Influencing Factors and Mediating Mechanisms of Job Crafting in Clinical Nursing Practice

Influencing Factors and Mediating Mechanisms of Job Crafting in Clinical Nursing Practice | 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 Influencing Factors and Mediating Mechanisms of Job Crafting in Clinical Nursing Practice Jia Wang, Yaru Li, Jiaxin Sun, Yajuan Cui, Mei Su, Peijuan Tang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7156066/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Job crafting plays a pivotal role in nursing management, with its optimization having the potential to enhance the quality of clinical care, the efficacy of healthcare organizations, and the multifaceted professional development of nurses. Design: A multi-center cross-sectional survey design was employed. Methods This study utilized a sample of 1,273 clinical nurses from tertiary hospitals in Inner Mongolia, China, selected through multistage sampling. To analyze the influencing factors and pathways, multiple linear regression and the Hayes PROCESS macro program (Models 4 and 6) were employed. Results The findings indicated that clinical nurses exhibited a moderately high level of job crafting, which was significantly influenced by career calling, extraversion, agreeableness, conscientiousness, and regulatory focus; extraversion and conscientiousness operated through the chain mediation of career calling and regulatory focus; whereas agreeableness was mediated through a singular mediation pathway of regulatory focus. This finding elucidates the mechanism by which personality traits differentially influence occupational behavior. Conclusions The study identifies multiple factors affecting nurses' job crafting. It is imperative for nursing managers to comprehensively consider these factors and develop a targeted monitoring system to effectively enhance nurses' capacity for job crafting. Clinical trial number: not applicable. Nurses job crafting career calling TIPI-C chain mediation Figures Figure 1 Figure 2 1. Introduction Job crafting refers to the proactive behavior of individuals who take the initiative to modify the nature and manner of their work. It has been recognized as a positive factor in both academic research and social contexts. Research indicates that job crafting can enhance work engagement(1), stimulate innovative behaviors(2), and increase organizational commitment(3). The International Labour Organization's Decent Work Country Programme for China (2023-2025) highlights proactive job crafting as a crucial strategy for promoting employee empowerment and establishing a sustainable work system(4). Nevertheless, job crafting presents challenges within the nursing profession. Nurses' capacity to reimagine their careers is significantly constrained by their prolonged exposure to high-stress environments characterized by illness, disability, and death. Data indicate that nurses lacking the ability to actively reshape their careers experience a 41% higher incidence of burnout compared to those who engage in job crafting, and they exhibit markedly lower job satisfaction(5). This deficiency in job crafting competence leads to rigidity in nursing processes, hinders clinical innovation, and results in role maladjustment, thereby perpetuating a detrimental cycle of “ Nursing Efficacy Deficit”. The World Health Organization (WHO) has highlighted the escalating crisis in nursing human resources, projecting a global shortage of over 7.6 million nurses by 2030(6), which underscores the critical need to strengthen nurses' competencies in reshaping their work roles. To optimize the management of nursing human resources and enhance professional efficacy, it is essential to identify the factors influencing nurses' job crafting. Numerous studies have demonstrated that nurses' job crafting behaviors are affected by a variety of factors. For instance, research conducted on ICU nurses in Beijing indicated that those possessing a bachelor's degree or higher were more inclined to enhance their sense of value by restructuring their work tasks and cognitive frameworks(7). Conversely, nurses in suboptimal health conditions tended to reduce their workloads to maintain psychological equilibrium(8). Additionally, family structure significantly influenced job crafting, as nurses with young children frequently employed strategies to mitigate work-family conflicts by optimizing their shift schedules(9). It is important to acknowledge that, while existing studies have elucidated the impact of explicit factors such as educational attainment and health status on nurses' job crafting, there remains a gap in understanding the underlying psychological mechanisms. Grounded in the theoretical framework of the Job Demand-Resource Model (JD-R), this study introduces three principal variables: personality traits, career calling, and regulatory focus. The objective is to examine the interaction effects of these variables within the JD-R framework, considering the dimensions of individual differences, intrinsic motivation, and cognitive regulation. Personality traits, as stable psychological characteristics, elucidate the fundamental differences in nurses' behaviors, such as cognitive crafting and relational crafting. Career calling, defined as an individual's sense of mission and meaning in the nursing profession, enhances the initiative and goal orientation associated with job crafting(10). Furthermore, regulatory focus reveals the varied response patterns of individuals to job resources and demands, characterized by cognitive dispositions oriented towards achieving success (promotion focus) or avoiding failure (prevention focus), thus highlighting differential response patterns to resources and demands(11).Therefore, the present study aims to examine the factors influencing job crafting among clinical nurses and to further explore the impact of personality traits on job crafting within the framework of the JD-R theory. Additionally, the study investigates the mediating roles of career calling and regulatory focus. The findings are intended to identify specific intervention targets for nursing human resource management to enhance the quality of nursing care. 2. Background The concept of "job crafting" was initially introduced by Dutton( 3 ), focusing on the dynamic process of individual value creation through task, relationship, and cognitive crafting. Empirical research indicates a strong association between job crafting and nursing groups, with such spontaneous job adjustment behaviors being prevalent( 8 ). Effective job crafting by nurses not only mitigates burnout but also enhances their sense of belonging to the hospital, ultimately yielding dual benefits: improved quality of nursing services and enhanced patient recovery( 9 , 12 ). Consequently, it has been termed the "stabilizer of nursing quality." Job crafting has emerged as a crucial strategy for optimizing the effectiveness of nursing teams. Studies demonstrate that this proactive behavior, involving flexible adjustments in work content, interpersonal relationships, and cognitive perspectives, can significantly enhance nurses' performance and stress resilience( 13 ). Furthermore, practices across various clinical settings have shown that emergency department nurses effectively reduced burnout risk by reorganizing task divisions( 14 ); during the epidemic, young nurses in rural hospitals in the United States notably enhanced their work engagement by altering their perceptions of stress( 15 ). Moreover, by strategically distributing work tasks and optimizing workflow, nurses can manage workloads more effectively, resulting in reduced burnout and increased job satisfaction( 16 ). A deficiency in the ability to reorganize work can lead to diminished quality of care, lower job satisfaction among nurses, and increased turnover rates( 12 , 17 ). Numerous factors influence job crafting among nurses. The JD-R theory, a pivotal framework for understanding occupational stress and employee well-being, underscores the significance of the dynamic equilibrium between demands and resources in the work environment on individual behavior( 18 ). According to this theory, job demands exhaust an individual's psychological resources, whereas job resources alleviate stress and foster positive psychological states. In 2017, the JD-R theory was applied to investigate job crafting within the nursing profession( 19 ). It was observed that when nurses proactively modified their job content through strategies such as task expansion and skill optimization, their control over resources increased, thereby reducing the risk of burnout associated with high job demands. Furthermore, it was found that nurses employed in healthcare institutions with robust organizational support systems were more adept at transforming work resources into career satisfaction and diminishing the inclination to leave due to resource depletion by engaging in knowledge sharing through teamwork( 20 ). According to the JD-R theory, personality traits constitute a significant individual resource and a pivotal factor in job crafting. These traits are encapsulated within five core dimensions in psychology that delineate individual personality differences: extraversion, conscientiousness, openness, emotional stability, and agreeableness. Personality traits influence nurses' professional adjustment, job performance, and the quality of patient care by impacting characteristics such as emotional stability, social tendencies, and a sense of responsibility. Research indicates that extraversion facilitates role reconfiguration by expanding social networks( 21 ); conscientiousness enables nurses to maintain efficient performance in complex tasks through goal-directed self-regulation( 22 ); openness fosters creative adaptation, thereby enhancing the development of individualized care plans( 21 ); and emotional stability mitigates the adverse effects of workplace uncertainty through stress buffering( 23 ). These findings underscore the differential impact of diverse personality traits on nursing career crafting behaviors. Individuals' personality traits are intrinsically linked to their career calling by shaping their perception of vocational significance. This profound value identity, in turn, reinforces their vocational commitment and adaptability, thereby establishing a virtuous cycle of trait-motivation( 24 ). The concept of career calling, defined as an individual's profound and meaningful connection to the nursing profession, serves as a continuous source of motivation for job crafting by internalizing altruistic values and fostering a sense of mission( 10 ). Unlike stable personality traits, career calling exhibits considerable dynamic adaptability. Nurses with a strong sense of career calling are capable of transforming standardized procedures into opportunities for patient empowerment, establishing therapeutic alliances in nurse-patient interactions, and redefining burdensome tasks into practices of life-care( 25 , 26 ). This meaning-driven reframing behavior generates a dual buffering effect, mitigating the detrimental impact of emotional exhaustion on work engagement and overcoming institutional constraints through the re-engineering of psychological contracts. In the highly collectivist context of China, however, the influence of career calling is further amplified by cultural factors. The Confucian ethic of benevolence and love aligns with the organizational spirit of dedication, elevating nurses' professional mission to encompass the upholding of family honor and the fulfillment of social roles( 27 ). According to the JD-R theory, the interaction between an individual's career calling and available job resources leads to the development of goal strategies aimed at achieving career value identity. Regulatory focus, a prominent framework for goal strategy, encapsulates the fundamental motivations of striving for growth or avoiding risks in career pursuits( 11 ). The process of behavioral decision-making following a career calling, which involves seeking meaning, varies according to specific regulatory focus pathways. Empirical evidence indicates that nurses with a promotion focus are more proficient at converting career-related pressures into opportunities for growth, exhibiting significantly higher levels of career satisfaction and innovative behaviors compared to those with a prevention focus( 28 , 29 ). Promotion focus has been found to have a significant positive correlation with job crafting behaviors, while prevention focus is linked to adaptive crafting( 30 ). Moreover, longitudinal research utilizing two-year follow-up data suggests that a prevention focus attenuates the positive effects of job crafting on career growth, whereas a promotion focus enhances this relationship( 31 ). Consequently, regulatory focus serves as a crucial moderator in the context of job crafting. In conclusion, the process of job crafting among nurses is shaped by a multitude of factors; however, existing research predominantly examines the independent impact of individual factors and lacks a comprehensive analysis of the synergistic effects of multiple factors. Consequently, this study aims to address the following three core questions from an integrative perspective: What are the characteristics of the current level of job crafting within the nursing population, and are there differences across groups? What factors influence nurses' job crafting? Are there interactions among these various influencing factors? This study proposes to employ a three-dimensional analytical framework (status quo-motivators-mechanisms) to overcome the limitations of single-factor research, provide a scientific foundation for nursing managers to develop systematic intervention strategies, and simultaneously advance the theoretical understanding of job crafting within healthcare contexts. 3. Methods 3.1. Aims To investigate the factors influencing job crafting levels among clinical nurses and elucidate the internal mechanisms linking personality traits to job crafting. 3.2. Study Design and Participants A multicenter cross-sectional study was conducted from February to March 2025 in Inner Mongolia, China. The sample size was determined using the standard formula for cross-sectional studies: n = Z 2 × p ×(1 − p )/ e 2 , where Z represents the Z-score corresponding to the desired confidence level (commonly 1.96 for a 95% confidence interval), p denotes the anticipated proportion (set at 0.5 to ensure the maximum sample size), and e signifies the allowable margin of error (typically 5%, or 0.05). Substituting these values into the formula yields an initial sample size of approximately 384. To account for the design effect associated with cluster sampling, the sample size is typically increased by a factor of 1.5 to 2, resulting in an adjusted sample size range of 576 to 768. This study employed a three-stage stratified sampling method. Initially, six league cities/prefecture-level cities were stratified based on the regional divisions of the Inner Mongolia into eastern, central, and western regions. Subsequently, 12 tertiary-level hospitals were stratified according to the distribution of regional tertiary-level hospitals. Finally, within the selected hospitals, nurses were chosen using a cluster sampling method, stratified by hospital size (number of beds) and department type. A detailed description of the sampling method is provided in Supplementary File 1. Ultimately, 1,273 nurses were selected. The inclusion criteria were: ( 1 ) registered nurses with a valid nursing practice certificate; ( 2 ) a minimum of one year of clinical work experience; and ( 3 ) informed consent and voluntary participation. The exclusion criteria were: ( 1 ) registered nurses undergoing training, further education, or internships; ( 2 ) absence from work during the survey period due to reasons such as vacation, study leave, illness, or childbirth; and ( 3 ) inability to complete the survey, such as experiencing a major life event. This cross-sectional study was conducted in accordance with the STROBE guidelines. The completed checklist is provided as supplementary material (STROBE-checklist-v4-cross-sectional.pdf). 3.3. Data Collection This study utilized the web-based platform Questionnaire Star ( https://www.wjx.cn/ ) for data collection, ensuring data validity and reliability through rigorous quality control measures. During the questionnaire design phase, the initial version was developed and refined based on a comprehensive literature review and expert consultation. In the distribution and retrieval phase, measures were implemented to enhance data integrity, including restricting submissions to a single device IP, binding responses to WeChat IDs to prevent duplicates, and imposing a minimum submission duration of 90 seconds to deter rapid response behaviors. During the data processing phase, invalid data, such as mechanical responses, logical inconsistencies, attention errors, and excessive missing values, were systematically excluded. Ultimately, 1,446 questionnaires were collected, and after thorough screening, 1,273 valid questionnaires were retained, resulting in an effective response rate of 88.04%. 3.4. Instruments 3.4.1. Demographic and Sociological Factors: Following an extensive review of the literature, the research team developed and administered a comprehensive general information questionnaire. This questionnaire encompassed various variables, including department type, ethnicity, age, gender, education level, marital status, professional title, job position, night shifts per month, total years of work experience, employment status, self-perceived health status, and frequency of off-site training per year. 3.4.2. Job Crafting Scale: This scale is a multidimensional assessment tool originally developed by Dvorak's team( 32 ) and subsequently adapted for cross-cultural contexts by Zhu Shixiao's team( 33 ). It comprises three sub-dimensions: relational crafting, task crafting, and cognitive crafting, with a total of 21 items. Responses are measured on a 5-point Likert scale (1 = strongly disagree, 5 = strongly agree), with the aggregate score indicating the individual's level of job crafting. The original scale demonstrated an internal consistency coefficient of 0.910, which was enhanced to 0.978 in the present study, with a Guttman split-half coefficient of 0.922. 3.4.3. The Career Calling Scale: This scale derived from Dobrow's theoretical framework( 34 ), has been adapted into Chinese by Pei Yujing and colleagues( 35 ). This 12-item instrument employs a 5-point Likert scale, featuring representative items such as "I am willing to make sacrifices for my current job." The original scale demonstrated a reliability coefficient of 0.940, while the current study reported a Cronbach's α of 0.976 and a Guttman split-half coefficient of 0.963, indicating a high level of reliability. 3.4.4. Nurse Regulatory Focus Scale (NRFQ): NRFQ was originally developed by Wallace( 36 ) and subsequently localized and validated by Li Shuying's team( 37 ). This scale is structured into two dimensions: promotion focus and prevention focus. It comprises 12 items, each rated on a 5-point Likert scale, yielding a total score range of 12 to 60. In the present study, the scale demonstrated high internal consistency, with a Cronbach's alpha of 0.973 and a Guttman split-half coefficient of 0.952. These metrics indicate the scale's efficacy in distinguishing the behavioral characteristics of caregivers with varying regulatory focus orientations. 3.4.5. The Psychological Capital Questionnaire: The Chinese version of Luthans' classic scale( 38 ) was validated for applicability to nursing groups by Luo Hong's team( 39 ). This instrument encompasses 20 items across four dimensions: self-efficacy, hope, resilience, and optimism, and is rated on a 6-point scale. The overall reliability of the scale was 0.923, with subscale alpha coefficients ranging from 0.718 to 0.890, and a test-retest reliability of 0.819. In this study, the Cronbach's alpha was found to be 0.989 and a Guttman split-half coefficient of 0.977, indicating excellent reliability. 3.4.6. Ten-Item Personality Inventory in China (TIPI-C): This scale was developed following the methodology established by Gosling( 40 ). This inventory, validated by Li Jinde( 41 ), utilizes a 10-item condensed version of the personality assessment tool to evaluate dimensions such as extraversion, agreeableness, conscientiousness, emotional stability, and openness, using a 7-point scale (1 = absolute disagreement, 7 = absolute agreement). Items 1, 3, 5, 7, and 9 are scored positively, while the remaining items are scored negatively. Each personality dimension is represented by a specific combination of items; for example, extraversion is assessed using items 1 and 6. The Cronbach's α for this inventory was measured as 0.855 and a Guttman split-half coefficient of 0.882. 3.5. Data Analysis Data organization was conducted using Microsoft Excel 2019, while statistical analyses were performed using SPSS Statistics version 24.0. Categorical variables were presented as frequency (n) and composition ratio (%). The normality of continuous variables was assessed using the Kolmogorov-Smirnov test. Variables following a normal distribution were expressed as mean ± standard deviation (M ± SD), whereas non-normally distributed data were represented by the median and interquartile range (M[Q1, Q3]). For continuous variables adhering to a normal distribution, analyses were conducted using the independent samples t-test for two groups or one-way analysis of variance (ANOVA) for multiple groups. Pearson's correlation coefficient was employed for bivariate normally distributed data, while Spearman's rank correlation coefficient was utilized for non-normally distributed data. Multiple linear regression models were developed to address multicollinearity, ensuring a variance inflation factor (VIF) of less than 5, and stepwise regression was applied for variable selection. Mediation effect analysis was conducted using the Bootstrap method with 5000 resamples, facilitated by the Hayes PROCESS macro program (Models 4 and 6). 4. Results 4.1. Descriptive and Univariate Analysis A total of 1,273 nurses participated in the study, ranging in age from 21 to 59 years, with a mean age of 34.81 years (SD = 7.12). Of these, 371 (29.1%) were internal medicine nurses, 272 (21.4%) were surgical nurses, 152 (11.9%) were obstetrics and gynecology nurses, 55 (4.3%) were pediatric nurses, 184 (14.5%) were employed in emergency, critical care, and intensive care unit, and 239 (18.8%) were from other departments. The study's findings indicated that factors such as gender, department, education level, professional title, job position, night shifts per month, total years of work experience, self-perceived health status, and frequency of off-site training per year significantly influenced clinical nurses' job crafting. As demonstrated in Table 1 , all observed differences were statistically significant ( p < 0.05). Post hoc multiple comparisons revealed that nurses with an associate degree or below exhibited significantly higher levels of job crafting compared to those with a bachelor's degree; job crafting was significantly higher among nurses with primary and senior titles compared to those with intermediate titles; job crafting was significantly more prevalent among nurses who worked ≤ 4 night shifts per month compared to those working 5ཞ9 shifts per month; nurses with 10 years of experience; nurses who perceived themselves as having better health reported higher levels of job crafting; the frequency of training also played a role; nurses who participated in training twice a year demonstrated significantly higher job crafting than those who attended training once a year, refer to Supplementary File 2. Table 1 Single factor analysis n (%) Job crafting(score, Mean ± SD) t/F P Gender Male 65(5.1%) 86.48 ± 18.26 3.543 0.001 Female 1208(94.9%) 78.27 ± 16.91 Department Internal medicine 371(29.1%) 76.75 ± 16.85 3.307 0.006 Surgery 272(21.4%) 80.25 ± 17.64 Obstetrics and gynecology 152(11.9%) 80.52 ± 16.93 Pediatrics 55(4.3%) 82.49 ± 15.54 Emergency, critical care, and intensive care unit 184(14.5%) 76.21 ± 16.51 Other departments 239(18.8%) 79.79 ± 17.21 Ethnicity Han Chinese 1037(81.5%) 78.86 ± 16.92 1.404 0.240 Mongolian 182(14.3%) 78.19 ± 16.56 Hui Chinese 18(1.4%) 83.33 ± 17.59 Other ethnic groups 36(2.8%) 74.08 ± 22.65 Education level Associate degree or below 143(11.2%) 82.65 ± 18.83 7.019 0.001 Bachelor's degree 1119(87.9%) 78.07 ± 16.78 Master's degree or above 11(0.9%) 89.91 ± 12.19 Marital status Unmarried 299(23.5%) 80.07 ± 19.00 2.569 0.077 Married without children 164(12.9%) 80.21 ± 16.58 Married with children 810(63.6%) 77.87 ± 16.38 Professional title Primary 545(42.8%) 80.58 ± 18.53 8.086 <0.001 Intermediate-level 499(39.2%) 76.38 ± 16.66 Senior-level 229(18.0%) 79.21 ± 13.42 Job position Nurse 1183(92.9%) 78.42 ± 17.27 -2.482 0.015 Head Nurse 90(7.1%) 82.23 ± 13.78 Night shifts per month ≤ 4 times 479(37.6%) 80.29 ± 15.94 3.639 0.027 5ཞ9 times 665(52.2%) 77.54 ± 17.26 >9 times 129(10.1%) 78.65 ± 19.62 Total years of work experience 10 years 689(54.1%) 77.59 ± 15.85 Employment status Non-established Position 942(74.0%) 78.97 ± 17.36 1.003 0.316 Established Position 331(26.0%) 77.88 ± 16.22 Self-perceived health status Excellent 525(41.2%) 86.26 ± 17.16 74.444 <0.001 Very good 349(27.4%) 77.53 ± 14.22 Good 327(25.7%) 71.43 ± 13.64 Fair 64(5.0%) 64.23 ± 14.63 Poor 8(0.6%) 44.5 ± 14.76 Frequency of off-site training per year 1 times 1145(89.9%) 78.29 ± 17.10 3.522 0.015 2 times 68(5.3%) 85.16 ± 12.56 3 times 15(1.2%) 77.73 ± 23.58 4 times or more 45(3.5%) 79.33 ± 18.28 4.2. Analysis of the Current Status of Job Crafting Among Nurses As indicated in Table 2 , the extent of job crafting among clinical nurses was moderate. A one-sample t-test analysis revealed that the mean scores for job crafting, career calling, regulatory focus, psychological capital, and the five personality traits were significantly above the theoretical median. These findings suggest that the nursing cohort possesses a more favorable self-assessment regarding their occupational psychological resources, such as psychological capital and regulatory focus, as well as their personality traits. Table 2 Analysis of the current situation Mean ± SD Test Statistic t-value Task crafting 3.51 ± 0.97 3.00 18.884 *** Cognitive crafting 3.85 ± 0.84 3.00 35.972 *** Relational crafting 3.88 ± 0.81 3.00 38.931 *** Job crafting 3.75 ± 0.81 3.00 32.785 *** Career calling 3.83 ± 0.85 3.00 34.823 *** Promotion focus 4.14 ± 0.71 3.00 57.418 *** Prevention focus 4.03 ± 0.73 3.00 50.225 *** Regulatory focus 4.09 ± 0.71 3.00 55.030 *** Self-Efficacy 4.86 ± 0.95 3.50 51.368 *** Hope 4.83 ± 0.95 3.50 50.141 *** Resilience 4.85 ± 0.94 3.50 51.121 *** Optimism 4.81 ± 1.05 3.50 44.609 *** Psychological capital 4.84 ± 0.93 3.50 51.456 *** Extraversion 5.07 ± 1.19 4.00 32.287 *** Agreeableness 4.52 ± 1.28 4.00 14.467 *** Conscientiousness 4.75 ± 1.17 4.00 22.697 *** Emotional stability 4.82 ± 1.18 4.00 24.791 *** Openness 5.04 ± 1.12 4.00 33.207 *** TIPI-C 4.84 ± 1.04 4.00 28.745 *** Note: *** represents p < 0.001. On the Likert 5 scale, a score of 3 represents neutrality, so the test value is 3; on the Likert 6 scale, a score of 3.5 represents neutrality, so the test value is 3.5; and on the Likert 7 scale, a score of 4 represents neutrality, so the test value is 4. 4.3. Pearson Correlation Analysis The Pearson correlation analysis results indicated that career calling, regulatory focus, psychological capital, and TIPI-C were all positively correlated with job crafting ( r = 0.797, p <0.01; r = 0.766, p <0.01༛ r = 0.772, p <0.01; r = 0.539, p <0.01), as detailed in Supplementary File 3. 4.4. Linear Regression Analysis We performed linear regression analyses using variables that demonstrated statistical significance ( p < 0.05) in the univariate analyses, including career calling, each of the TIPI-C dimensions, and nurse regulatory focus as independent variables, with nurse job crafting as the dependent variable. For categorical variables related to general information, dummy variables were assigned as described in Supplementary File 4. The regression analysis results revealed a good model fit, with an adjusted R -squared value of 0.689. This indicates that the independent variables in the regression model account for 68.9% of the variance in the dependent variable, suggesting that the current model effectively identifies the factors influencing job crafting. The findings indicated that several factors significantly influenced nurses' job crafting, including career calling, extraversion, agreeableness, conscientiousness, regulatory focus, department, educational level, self-perceived health, and gender. Specifically, nurses working in surgical, obstetrics and gynecology, and pediatrics departments exhibited significantly higher levels of job crafting compared to their counterparts in other departments. Additionally, nurses holding a master's degree or higher demonstrated significantly greater job crafting than those with an associate degree or below. Conversely, nurses with very poor health engaged in significantly less job crafting compared to those with good health. Furthermore, female nurses exhibited significantly lower levels of job crafting than their male counterparts (Table 3 ). Table 3 Linear regression analysis Unstandardized Coefficients Standardized Coefficients t-value p-value VIF (constant) 8.905 3.432 0.001 Department Internal medicine 0.420 0.011 0.503 0.615 1.988 Surgery 1.962 0.047 2.214 0.027 1.819 Obstetrics and gynecology 2.893 0.055 2.767 0.006 1.585 Pediatrics 3.597 0.043 2.456 0.014 1.223 Emergency, critical care, and intensive care unit 0.645 0.013 0.648 0.517 1.693 Other departments 0 Education level Bachelor's degree 0.021 0.000 0.023 0.982 1.222 Master's degree or above 6.189 0.034 1.976 0.048 1.159 Associate degree or below 0 Professional title Intermediate-level -1.311 -0.037 -1.756 0.079 1.832 Senior-level -0.999 -0.022 -1.001 0.317 2.028 Primary 0 Night shifts per month 5ཞ9 times 0.225 0.007 0.341 0.733 1.496 >9 times -0.959 -0.017 -0.944 0.345 1.295 ≤ 4 times 0 Total years of work experience 3ཞ5 years 1.047 0.018 0.902 0.367 1.574 6ཞ10 years 0.368 0.009 0.362 0.717 2.504 >10 years -0.836 -0.024 -0.823 0.411 3.532 <3 years 0 Self-perceived health status Very good -1.327 -0.035 -1.893 0.059 1.349 Good -0.891 -0.023 -1.148 0.251 1.584 Fair -0.334 -0.004 -0.240 0.811 1.276 Poor -8.280 -0.038 -2.324 0.020 1.094 Excellent 0 Frequency of off-site training per year 2 times 1.736 0.023 1.355 0.176 1.145 3 times 1.171 0.007 0.457 0.648 1.058 4 times or more 0.674 0.007 0.455 0.649 1.031 1 times 0 Gender Female -2.984 -0.038 -2.337 0.020 1.090 Male 0 Job position Head nurse 0.697 0.010 0.573 0.566 1.339 Nurse 0 Career calling 0.741 0.444 13.360 0.000 4.429 Extraversion 0.514 0.071 2.616 0.009 2.998 Agreeableness 0.567 0.085 2.811 0.005 3.693 Conscientiousness -0.440 -0.060 -2.048 0.041 3.502 Emotional stability 0.260 0.036 1.240 0.215 3.363 Openness -0.001 0.000 -0.003 0.998 2.981 Nurse regulatory focus 0.614 0.304 10.006 0.000 3.714 Adjusted R-squared 0.683 F 92.538 p <0.001 Note: The dependent variable was job crafting. Due to the strong covariance observed between the dimensions of nurses' regulatory focus (promotion focus and prevention focus), psychological capital, and their respective dimensions, these variables were excluded from the linear regression analysis as independent variables to ensure the accuracy of the results. 4.5. Mediating Effect Analysis To further investigate the potential interaction effect between various influences and job crafting, this study employed path analysis. The findings from the double-chain mediation model revealed that the overall impact of extraversion and conscientiousness on job crafting was significant( β = 4.305, p < 0.001; β = 3.074, p < 0.001), suggesting that higher levels of extraversion and conscientiousness are associated with more robust job crafting behaviors. Even after controlling for mediating variables, extraversion and conscientiousness continued to exert a significant positive effect on job crafting( β = 0.856, p < 0.001; β = 0.420, p < 0.01), albeit with a reduced effect size, indicating partial mediation. The model fit was strong, with the regression models for career calling, regulatory focus, and job crafting yielding R² values of 0.419/0.213, 0.716/0.714, and 0.673/0.668, respectively. Bootstrap analysis with 5000 iterations confirmed the robustness of the results, as all confidence intervals for indirect effects excluded zero. Career calling emerged as the primary mediator, with its individual mediating effects (Ind1) accounting for 49.81% and 54.64% of the total indirect effects, respectively. This indicates that extraversion and conscientiousness primarily enhance job crafting through the enhancement of career calling. The chain mediation effect (Ind3) was significant, indicating that extroversion and conscientiousness influenced moderating focus via career calling, which subsequently impacted job crafting. This accounted for 26.38% and 28.83% of the total indirect effect, respectively. Although the independent mediating effect of moderating focus was relatively weak, contributing only 3.92% and 2.86% for Ind2, it served a complementary function within the chain pathway. The mediating effect of career calling was considerably stronger than the independent mediation effect of moderating focus. Furthermore, the direct effect of career calling was more pronounced than its chained effect through moderating focus, and the chained mediation effect was significantly more robust than the independent mediation of moderating focus (refer to Table 4 , Figs. 1 a and 1 b). According to the analysis of a simple mediation model, the total effect of agreeableness on job crafting was found to be significant ( β = 3.117, p < 0.001), suggesting that increased agreeableness is associated with enhanced job crafting behavior. Even after accounting for mediating variables, agreeableness continued to exert a significant positive influence on job crafting ( β = 1.223, p < 0.001), although the effect size was diminished, indicating the presence of partial mediation. The mediating effect was quantified at 1.894, representing 60.77% of the total effect. The model fit was demonstrated by the regression models for moderating focus and job crafting, which exhibited R² values of 0.170 and 0.615, respectively, indicating strong explanatory power. Bootstrap analysis with 5000 iterations revealed that the confidence intervals for all indirect effects did not include zero, confirming the robustness of the findings (refer to Table 4 and Fig. 2). Table 4 Path diagram Effect BootSE BootLLCI BootULCI Effect Proportion Path 1 Total 3.449 0.160 3.132 3.749 80.11% Ind1: extraversion ->career calling ->job crafting 2.145 0.168 1.810 2.472 49.81% Ind2: extraversion ->regulatory focus ->job crafting 0.169 0.058 0.061 0.288 3.92% Ind3: extraversion ->career calling ->regulatory focus->job crafting 1.136 0.138 0.865 1.409 26.38% Ind1- Ind2 1.976 0.188 1.600 2.339 – Ind1- Ind3 1.009 0.269 0.461 1.530 – Ind2- Ind3 -0.967 0.138 -1.258 -0.709 – Path 2 Total 2.653 0.166 2.329 2.979 86.33% Ind1: conscientiousness ->career calling ->job crafting 1.679 0.141 1.412 1.962 54.64% Ind2: conscientiousness ->regulatory focus->job crafting 0.088 0.045 0.004 0.179 2.86% Ind3: conscientiousness ->career calling ->regulatory focus ->job crafting 0.886 0.111 0.676 1.113 28.83% Ind1- Ind2 1.591 0.149 1.302 1.893 – Ind1- Ind3 0.793 0.201 0.387 1.178 – Ind2- Ind3 -0.798 0.109 -1.027 -0.595 – Path 3 agreeableness ->regulatory focus ->job crafting 1.894 0.1344 1.6217 2.1579 60.77% 5. Discussion 5.1. Analysis of the Current Status of Nurses' Job crafting and Group Differences This study determined that the extent of job crafting among clinical nurses was moderately high, aligning with the findings of Park( 42 ). The average age of the nurses was 34.81 years (SD = 7.12), indicating a relatively youthful nursing workforce in Inner Mongolia, China. This age distribution may influence the patterns of job crafting differently. Younger nurses demonstrated a greater propensity to meet professional demands through task crafting, whereas older nurses tended to focus on relational crafting. This observation is consistent with Zhang's research( 43 ) on age stratification among nursing staff. Furthermore, the level of task crafting was notably higher among nurses with less than three years of experience compared to other groups. This finding supports Benner's theory of novice development, which suggests that new nurses develop clinical competence by actively adapting their work styles during the process of occupational socialization( 44 ). The level of job crafting significantly declined among individuals in the 6ཞ10 years experience group, indicating a heightened risk of burnout at this career stage and underscoring the necessity to avoid the "mid-career trap." This observation aligns with the U-shaped distribution of professional title: nurses with primary title exhibited greater motivation for crafting, driven by the need for career exploration; those with senior title often engaged in clinical teaching and systemic change initiatives, leveraging their professional authority; whereas nurses with intermediate title experienced role overload due to the demands of developing their specialties, leading to diminished motivation for crafting( 45 – 47 ). Furthermore, nurses working low-frequency night shifts (≤ 4 times per month) demonstrated significantly higher levels of job crafting compared to those in the high-frequency group (5ཞ9 times). This suggests that frequent disruptions to circadian rhythms may inhibit proactive change behaviors by depleting psychological resources. This finding corroborates the research of Van( 48 , 49 ) on the cognitive load experienced by shift-based nursing staff. The findings indicate that the impact of continuing education exhibits a nonlinear characteristic, with the biannual out-of-home training cohort demonstrating superior performance. This suggests that a moderate frequency of training, when combined with high-quality content, is more effective in enhancing occupational adaptability than merely increasing the frequency of training sessions. Zhuang's study( 50 ) corroborates this by indicating that training frequency surpassing a certain threshold may induce learning fatigue, thereby diminishing the effectiveness of knowledge translation. Collectively, these findings suggest that job crafting within a young, highly mobile nursing workforce results from the dynamic interplay between individual attributes and the organizational environment. Future research should focus on examining the moderating effects of contextual factors, such as department type, to refine the implementation strategies for career development interventions. 5.2. Analysis of Factors Influencing Nurses' Job Crafting In alignment with the JD-R theory proposed by Shan( 51 ), the data from this study indicate that nurses' job crafting behaviors are systematically influenced by both environmental resources (such as the departments) and individual resources (including gender, education, perceived health, personality traits, career calling, and regulatory focus). At the environmental level, surgical nurses have notably enhanced work efficiency through task integration, corroborating Jakobsson's( 52 ) conclusions regarding adaptive strategies in high-stress units. In contrast, obstetrics and gynecology nurses are required to develop communication patterns that emphasize the agreeableness of personality, tailored to the unique characteristics of the population they serve. Interestingly, the occurrence of innovative behaviors among pediatric nurses was significantly higher than typically anticipated, contradicting Zelesniack's( 53 ) assertion that due conscientiousness inhibits innovation. This discrepancy may be attributed to the special needs of pediatric patients, which could potentially diminish the impact of professional normative constraints. These findings indicate that clinical managers should implement tailored training programs that reflect the cultural characteristics of their respective departments. For instance, intensive multitasking coordination training could be beneficial in surgical settings, empathy communication workshops may enhance interactions in obstetrics and gynecology, and the introduction of fault-tolerance mechanisms could foster innovative practices in pediatrics. At the individual level, this study elucidated the structural differentiation mechanism of gender and education on nurses' job crafting. The findings indicated that female nurses encountered cognitive resource allocation dilemmas due to role conflicts between family and profession, aligning with the theory of occupational gender role solidification( 54 ). In contrast, male nurses proactively constructed their professional identities by competing for technical positions, a strategic approach consistent with the findings of Younas( 55 ). The educational level exhibited a U-shaped distribution in relation to job crafting behaviors, nurses with a master's degree or higher demonstrated a strong propensity to reinvent themselves based on their professional strengths, aiming for higher career achievements( 56 ). Conversely, nurses with an associate degree or below engaged in practical crafting behaviors, driven by accumulated experience and the pressure of challenges( 57 ). Nurses with a bachelor's degree experienced a crafting trough, closely associated with career development bottlenecks, insufficient resource support, and deficiencies in the accreditation system; male nurses actively shape their professional identity through competition for technical positions, highlighting deficiencies in system articulation( 58 ). Further studies have demonstrated that career satisfaction and the work environment moderate crafting behaviors, with nurses holding bachelor's degrees being more susceptible to burnout in unsupportive settings( 59 ). These findings indicate the necessity for nursing management to develop a gender-sensitive support network to alleviate role conflicts experienced by female nurses. Additionally, there is a need to innovate the specialty certification system for bachelor's degree nurses to enhance their career vitality through career path reconstruction. At the individual level, career calling significantly and positively predicts nurses' job crafting levels, suggesting that nurses with a strong sense of career calling are more likely to proactively adjust their job content and roles. This observation aligns with the findings of Esteves( 60 ). In a comprehensive examination of the mechanisms underlying these phenomena, Solms( 61 ) identified that nurses develop psychological resilience through goal-oriented behaviors, such as proactive resource acquisition, which serve to effectively mitigate occupational stress. In the present study, it is suggested that nurses with a strong career calling may engage in job crafting via a similar mechanism. A pronounced sense of career calling not only augments nurses' career satisfaction but also diminishes burnout and turnover intentions. Empirical evidence indicates a robust correlation between a sense of career calling and nurses' job satisfaction, organizational commitment, and career development( 62 ). Furthermore, a sense of professional mission can bolster nurses' career success by enhancing their psychological resilience( 63 ). Within the context of nursing management, promoting nurses' sense of professional mission and psychological resilience is a crucial strategy for increasing career satisfaction and reducing turnover intentions( 64 ). Consequently, nursing managers should prioritize providing nurses with career development opportunities and support to strengthen their sense of professional mission and psychological resilience, thereby improving the overall quality of care and the ability of nurses to transform their work. At the individual level, regulatory focus is a significant and positive predictor of nurses' job crafting, indicating that nurses' personal regulatory tendencies influence how they redefine their roles. This finding is corroborated by Roczniewska's study( 65 ). Considering the highly dynamic nature of the nursing profession and the diverse needs of patients( 66 , 67 ), regulatory focus suggests that nurses with a promotion regulatory focus are inclined to pursue professional growth by exploring new responsibilities. In contrast, those with a prevention focus tend to avoid risks by optimizing existing processes, both of which contribute to job crafting( 68 ). Notably, this study found that the promotion focus dimension scored higher than the prevention focus, which may be attributed to the nursing professional culture that emphasizes achievement-oriented behaviors. Consequently, nursing managers can enhance nurses' regulatory focus through tailored strategies by providing innovative task platforms for promotion focus nurses and establishing a risk warning support system for prevention focus nurses, thereby optimizing job crafting behaviors. Future investigations should also differentiate regulatory focus dimensions to provide a more precise basis for decision-making in nursing human resource management. 5.3. Analysis of the Mediating Effects of Nurse Job Crafting We were intrigued to discover interaction effects between personality traits and career calling, as well as regulatory focus and job crafting. The results suggest that the traits of extraversion and conscientiousness predominantly influence job crafting behaviors through career calling, accounting for a substantial contribution of 49.81–54.64%, compared to a lesser contribution of 2.86–3.92% from regulatory focus focus. This finding provides cross-situational validation with Bakker's study( 13 ), which similarly demonstrates that career calling, as a fundamental intrinsic resource, possesses greater explanatory power in mitigating emotional depletion than regulatory focus. These disparities may be attributed to the contextual demands unique to the nursing profession( 69 ), where exposure to patient distress and cues of life vulnerability serve as persistent contextual stimuli that activate the empathic response network in extroverted individuals and the responsibility perception system in conscientious individuals. In particular, extraverted nurses prioritize forming affective connections over pursuing instrumental goals when expanding their social support networks. In contrast, conscientious nurses' involvement in quality improvement practices is strongly linked to their professional mission, particularly through the achievement of nursing safety goals( 70 , 71 ). This specific alignment of traits, situations, and goals not only accounts for variations in behavioral performance across different contexts but also underscores the moderating role of autonomous decision-making space and immediate feedback mechanisms in enhancing trait efficacy within the nursing profession. Furthermore, traits associated with agreeableness can substantially impact nurses' job crafting behaviors by regulatory focus mechanisms. Empirical evidence supports this assertion, highlighting the cooperative, empathetic, and altruistic dimensions of agreeableness( 23 , 72 , 73 ), which predispose highly agreeable nurses to pursue socially desirable objectives. This social orientation aligns naturally with the "growth" logic of promotion focus, prompting individuals to prioritize positive outcomes and thereby fostering proactive work crafting behaviors( 74 ). This facilitation mechanism is particularly pronounced in teamwork settings, where consistent leadership in facilitation orientation not only reinforces team identity but also significantly enhances the innovation effectiveness of nursing teams through goal synergy( 75 ). Nonetheless, it is crucial to acknowledge that the specific nature of nursing necessitates the concurrent fulfillment of therapeutic alliance building and medical risk aversion, resulting in the inevitable coexistence of prevention focus mechanisms( 76 ). Neuroimaging evidence indicates that individuals with robust prefrontal-limbic system connectivity exhibit superior focus-switching abilities in resuscitation scenarios, providing a neuroplasticity-based explanation for the transformation of traits into behaviors( 77 ). According to the JD-R theoretical framework, career calling and regulatory focus serve as key mediating variables in the relationship between personality traits and job crafting. The intrinsic mechanisms of these variables are demonstrated by the continuous activation of nurses' commitment to job crafting, facilitated by the dual motivational system of a sense of meaning and a sense of mission( 10 ). Concurrently, regulatory focus enhances the ability to identify opportunities through a success-oriented approach and optimizes risk decision-making by emphasizing the avoidance of failures [11]. Together, these factors create a synergistic closed-loop structure of "motivational stimulation-cognitive regulation." Consequently, nursing managers can enhance nurses' ability to construct meaning through occupational value strengthening training and improve their situational adaptation strategies via cognitive flexibility training. This approach ultimately leads to the progressive enhancement of individual resource empowerment and the effectiveness of job crafting. 6. Limitations This study possesses several limitations that warrant consideration. Firstly, the cross-sectional design hinders the establishment of causal time-series relationships between variables, necessitating future longitudinal studies to verify the long-term effects of personality traits on job crafting. Secondly, the sample was restricted to tertiary hospitals in Inner Mongolia, potentially limiting the generalizability of the findings to primary healthcare institutions and diverse cultural contexts. Lastly, the analysis of mediating mechanisms did not account for environmental variables such as organizational support, which may lead to an underestimation of the moderating role of the management context. Consequently, future research should construct a multilevel interaction model. 7. Conclusion The study indicated that the overall level of job crafting among clinical nurses was moderately high and was influenced by a variety of factors. At the individual level, variables such as gender, education level, self-perceived health status, personality traits, career calling, and regulatory focus significantly impacted job crafting performance. Environmentally, the job crafting abilities of nurses in the departments of surgery, obstetrics and gynecology, and pediatrics were notably higher compared to those in other departments. Among the personality traits, extraversion, agreeableness, and conscientiousness were strongly associated with job crafting. Further analysis demonstrated that extraversion and conscientiousness primarily facilitated job crafting behaviors through career calling, which played a predominant role in this process, while the moderating role of focus was limited. Additionally, agreeableness significantly influenced job crafting through the mechanism of moderating focus. Based on these findings, it is advisable for nursing managers to implement the following strategies: optimize job allocation by thoroughly considering the alignment between individual personality traits and specific job demands; facilitate cross-departmental exchanges to enhance nurses' ability to engage in job crafting within high-pressure environments; and develop a framework for fostering a sense of career calling while monitoring health status dynamics to promote the integrated management of psychological resources and job demands. Abbreviations Complete designation Abbreviation 1 World Health Organization WHO 2 Job Demand-Resource Model JD-R 3 Nurse Regulatory Focus Scale NRFQ 4 Ten-Item Personality Inventory in China TIPI-C 5 one-way analysis of variance ANOVA 6 variance inflation factor VIF Declarations Data Availability Statement The data that support the findings of this study are available from the corresponding author on reasonable request. Ethics approval and consent to participate This study was performed in accordance with the Declaration of Helsinki. The studies involving human participants were reviewed and approved by the Ethics Committee of the Inner Mongolia People's Hospital (202504004L). All participants gave informed consent and signed “yes” prior to data collection. Consent for publication Not applicable. Conflicts of Interest The authors declare no conflicts of interest. The funding agencies had no involvement in study design, data collection/analysis, manuscript preparation, or publication decisions. Author Contributions JW and YRL contributed to the conceptualization of the study, performed the analysis, wrote the manuscript; MS, YCH and PJT contributed significantly to investigation and project administration; YJC, YTW and JXS assisted with data curation; YLW and WZC contributed to the conceptualization of the study and reviewed the manuscript. All authors have read and approved the manuscript. Authors' information JW: Master's Candidate, Member of the Nursing Education Committee, Chinese Research Hospital Association, [email protected] YRL: Deputy Director of Nursing Department, Member, International Nursing Branch, Asia-Pacific Vascular Academic Alliance, [email protected] YLW: Director of Nursing, Member of the 28th Council of the Chinese Nursing Association, [email protected] WZC: Chief Nurse Executive, Standing Committee Member, Nursing Education Committee, Chinese Research Hospital Association, [email protected] Funding The study was supported by the Science and Technology Program of the Joint Fund of Scientific Research for the Public Hospitals of Inner Mongolia Academy of Medical Sciences (2023GLLH0055), the Science and Technology Program of the Joint Fund of Scientific Research for the Public Hospitals of Inner Mongolia Academy of Medical Sciences (2023GLLH0084), and Ordos Key Research and Development Program Project (YF20240064). 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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-7156066","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":494181424,"identity":"533fac13-6696-4b5b-8143-194b29a6841e","order_by":0,"name":"Jia Wang","email":"","orcid":"","institution":"Inner Mongolia People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jia","middleName":"","lastName":"Wang","suffix":""},{"id":494181425,"identity":"ae021e73-80f5-4a56-b642-b9ec16220310","order_by":1,"name":"Yaru Li","email":"","orcid":"","institution":"Ordos Traditional Chinese Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yaru","middleName":"","lastName":"Li","suffix":""},{"id":494181426,"identity":"e9651ba7-c384-449c-8776-b9d6b9865511","order_by":2,"name":"Jiaxin Sun","email":"","orcid":"","institution":"Affiliated Hospital of Inner Mongolia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiaxin","middleName":"","lastName":"Sun","suffix":""},{"id":494181427,"identity":"4cd16988-0189-40a6-9dac-98c5fa28bbca","order_by":3,"name":"Yajuan Cui","email":"","orcid":"","institution":"Inner Mongolia Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yajuan","middleName":"","lastName":"Cui","suffix":""},{"id":494181429,"identity":"03185330-0ab2-4819-a22e-75e33fe58a59","order_by":4,"name":"Mei Su","email":"","orcid":"","institution":"Inner Mongolia People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mei","middleName":"","lastName":"Su","suffix":""},{"id":494181430,"identity":"c8a08659-a211-4588-a93b-c1ad003fb3df","order_by":5,"name":"Peijuan Tang","email":"","orcid":"","institution":"Inner Mongolia People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Peijuan","middleName":"","lastName":"Tang","suffix":""},{"id":494181432,"identity":"3fd806fc-eee1-4ee9-b360-87a6b33db5e2","order_by":6,"name":"Yanting Wang","email":"","orcid":"","institution":"Inner Mongolia People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yanting","middleName":"","lastName":"Wang","suffix":""},{"id":494181433,"identity":"61f60109-5a56-49d3-8d13-29b67e88078e","order_by":7,"name":"Yuchong Hu","email":"","orcid":"","institution":"Inner Mongolia People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuchong","middleName":"","lastName":"Hu","suffix":""},{"id":494181435,"identity":"2ceb5bd5-0d49-479f-8642-afb6942f4252","order_by":8,"name":"Wenzhong Chang","email":"","orcid":"","institution":"Inner Mongolia People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Wenzhong","middleName":"","lastName":"Chang","suffix":""},{"id":494181437,"identity":"f665d487-64a7-4d55-a963-e427d301ebac","order_by":9,"name":"Yanli Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAxElEQVRIiWNgGAWjYFAC5uYHCQYSckAWG7FaGNsMPlRYGMO0SBCjpUFyxpmKxAaitRjcSGww5m2TSN9wvPnZA8YdNnVEaXkM1JK74cwxcwPGM2mEbTGD2pK74UaCmQRj22HitEiDHGZw//k3oJb/xGkBel8iweAGD8iWA4S12J95CApkCcOZZ3LKJBLbkiUbCGmRbE8+DIzKOnm+48e3SXxss+MnaAuDQAKEVjgAJBIIqwcC/gMQWp6gg0bBKBgFo2DEAgD3UUFyneyCQgAAAABJRU5ErkJggg==","orcid":"","institution":"Inner Mongolia People’s Hospital","correspondingAuthor":true,"prefix":"","firstName":"Yanli","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-07-18 09:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7156066/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7156066/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88323232,"identity":"64078ab5-0c61-4bfe-852d-3ec4ad463a17","added_by":"auto","created_at":"2025-08-05 09:19:36","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":117119,"visible":true,"origin":"","legend":"\u003cp\u003ea Diagram of the chain mediating effect of extraversion\u003c/p\u003e\n\u003cp\u003eb Diagram of the chain mediation effects of conscientiousness\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7156066/v1/8a4298e9821602106ceeb9e7.jpg"},{"id":88324322,"identity":"49af46cf-b2c9-421a-89ae-88642bfba705","added_by":"auto","created_at":"2025-08-05 09:27:36","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":31983,"visible":true,"origin":"","legend":"\u003cp\u003eDiagram of mediating effects of agreeableness\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7156066/v1/aab9201bb34f7cea8178e1f4.jpg"},{"id":91963712,"identity":"6a903964-7c2d-4628-8cba-c45a080306cb","added_by":"auto","created_at":"2025-09-23 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09:27:36","extension":"doc","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":36864,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile4.doc","url":"https://assets-eu.researchsquare.com/files/rs-7156066/v1/c05dac1e442df34fa90c79fb.doc"}],"financialInterests":"No competing interests reported.","formattedTitle":"Influencing Factors and Mediating Mechanisms of Job Crafting in Clinical Nursing Practice","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eJob crafting refers to the proactive behavior of individuals who take the initiative to modify the nature and manner of their work. It has been recognized as a positive factor in both academic research and social contexts. Research indicates that job crafting can enhance work engagement(1), stimulate innovative behaviors(2), and increase organizational commitment(3). The International Labour Organization\u0026apos;s Decent Work Country Programme for China (2023-2025) highlights proactive job crafting as a crucial strategy for promoting employee empowerment and establishing a sustainable work system(4). Nevertheless, job crafting presents challenges within the nursing profession. Nurses\u0026apos; capacity to reimagine their careers is significantly constrained by their prolonged exposure to high-stress environments characterized by illness, disability, and death. Data indicate that nurses lacking the ability to actively reshape their careers experience a 41% higher incidence of burnout compared to those who engage in job crafting, and they exhibit markedly lower job satisfaction(5). This deficiency in job crafting competence leads to rigidity in nursing processes, hinders clinical innovation, and results in role maladjustment, thereby perpetuating a detrimental cycle of \u0026ldquo; Nursing Efficacy Deficit\u0026rdquo;.\u0026nbsp;The World Health Organization (WHO) has highlighted the escalating crisis in nursing human resources, projecting a global shortage of over 7.6 million nurses by 2030(6), which underscores the critical need to strengthen nurses\u0026apos; competencies in reshaping their work roles.\u003c/p\u003e\n\u003cp\u003eTo optimize the management of nursing human resources and enhance professional efficacy, it is essential to identify the factors influencing nurses\u0026apos; job crafting. Numerous studies have demonstrated that nurses\u0026apos; job crafting behaviors are affected by a variety of factors. For instance, research conducted on ICU nurses in Beijing indicated that those possessing a bachelor\u0026apos;s degree or higher were more inclined to enhance their sense of value by restructuring their work tasks and cognitive frameworks(7). Conversely, nurses in suboptimal health conditions tended to reduce their workloads to maintain psychological equilibrium(8). Additionally, family structure significantly influenced job crafting, as nurses with young children frequently employed strategies to mitigate work-family conflicts by optimizing their shift schedules(9). It is important to acknowledge that, while existing studies have elucidated the impact of explicit factors such as educational attainment and health status on nurses\u0026apos; job crafting, there remains a gap in understanding the underlying psychological mechanisms.\u003c/p\u003e\n\u003cp\u003eGrounded in the theoretical framework of the Job Demand-Resource Model (JD-R), this study introduces three principal variables: personality traits, career calling, and regulatory focus. The objective is to examine the interaction effects of these variables within the JD-R framework, considering the dimensions of individual differences, intrinsic motivation, and cognitive regulation. Personality traits, as stable psychological characteristics, elucidate the fundamental differences in nurses\u0026apos; behaviors, such as cognitive crafting and relational crafting. Career calling, defined as an individual\u0026apos;s sense of mission and meaning in the nursing profession, enhances the initiative and goal orientation associated with job crafting(10). Furthermore, regulatory focus reveals the varied response patterns of individuals to job resources and demands, characterized by cognitive dispositions oriented towards achieving success (promotion focus) or avoiding failure (prevention focus), thus highlighting differential response patterns to resources and demands(11).Therefore, the present study aims to examine the factors influencing job crafting among clinical nurses and to further explore the impact of personality traits on job crafting within the framework of the JD-R theory. Additionally, the study investigates the mediating roles of career calling and regulatory focus. The findings are intended to identify specific intervention targets for nursing human resource management to enhance the quality of nursing care.\u0026nbsp;\u003c/p\u003e"},{"header":"2. Background","content":"\u003cp\u003eThe concept of \"job crafting\" was initially introduced by Dutton(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e), focusing on the dynamic process of individual value creation through task, relationship, and cognitive crafting. Empirical research indicates a strong association between job crafting and nursing groups, with such spontaneous job adjustment behaviors being prevalent(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Effective job crafting by nurses not only mitigates burnout but also enhances their sense of belonging to the hospital, ultimately yielding dual benefits: improved quality of nursing services and enhanced patient recovery(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Consequently, it has been termed the \"stabilizer of nursing quality.\"\u003c/p\u003e\u003cp\u003eJob crafting has emerged as a crucial strategy for optimizing the effectiveness of nursing teams. Studies demonstrate that this proactive behavior, involving flexible adjustments in work content, interpersonal relationships, and cognitive perspectives, can significantly enhance nurses' performance and stress resilience(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Furthermore, practices across various clinical settings have shown that emergency department nurses effectively reduced burnout risk by reorganizing task divisions(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e); during the epidemic, young nurses in rural hospitals in the United States notably enhanced their work engagement by altering their perceptions of stress(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Moreover, by strategically distributing work tasks and optimizing workflow, nurses can manage workloads more effectively, resulting in reduced burnout and increased job satisfaction(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). A deficiency in the ability to reorganize work can lead to diminished quality of care, lower job satisfaction among nurses, and increased turnover rates(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNumerous factors influence job crafting among nurses. The JD-R theory, a pivotal framework for understanding occupational stress and employee well-being, underscores the significance of the dynamic equilibrium between demands and resources in the work environment on individual behavior(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). According to this theory, job demands exhaust an individual's psychological resources, whereas job resources alleviate stress and foster positive psychological states. In 2017, the JD-R theory was applied to investigate job crafting within the nursing profession(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). It was observed that when nurses proactively modified their job content through strategies such as task expansion and skill optimization, their control over resources increased, thereby reducing the risk of burnout associated with high job demands. Furthermore, it was found that nurses employed in healthcare institutions with robust organizational support systems were more adept at transforming work resources into career satisfaction and diminishing the inclination to leave due to resource depletion by engaging in knowledge sharing through teamwork(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to the JD-R theory, personality traits constitute a significant individual resource and a pivotal factor in job crafting. These traits are encapsulated within five core dimensions in psychology that delineate individual personality differences: extraversion, conscientiousness, openness, emotional stability, and agreeableness. Personality traits influence nurses' professional adjustment, job performance, and the quality of patient care by impacting characteristics such as emotional stability, social tendencies, and a sense of responsibility. Research indicates that extraversion facilitates role reconfiguration by expanding social networks(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e); conscientiousness enables nurses to maintain efficient performance in complex tasks through goal-directed self-regulation(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e); openness fosters creative adaptation, thereby enhancing the development of individualized care plans(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e); and emotional stability mitigates the adverse effects of workplace uncertainty through stress buffering(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). These findings underscore the differential impact of diverse personality traits on nursing career crafting behaviors. Individuals' personality traits are intrinsically linked to their career calling by shaping their perception of vocational significance. This profound value identity, in turn, reinforces their vocational commitment and adaptability, thereby establishing a virtuous cycle of trait-motivation(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe concept of career calling, defined as an individual's profound and meaningful connection to the nursing profession, serves as a continuous source of motivation for job crafting by internalizing altruistic values and fostering a sense of mission(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Unlike stable personality traits, career calling exhibits considerable dynamic adaptability. Nurses with a strong sense of career calling are capable of transforming standardized procedures into opportunities for patient empowerment, establishing therapeutic alliances in nurse-patient interactions, and redefining burdensome tasks into practices of life-care(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). This meaning-driven reframing behavior generates a dual buffering effect, mitigating the detrimental impact of emotional exhaustion on work engagement and overcoming institutional constraints through the re-engineering of psychological contracts. In the highly collectivist context of China, however, the influence of career calling is further amplified by cultural factors. The Confucian ethic of benevolence and love aligns with the organizational spirit of dedication, elevating nurses' professional mission to encompass the upholding of family honor and the fulfillment of social roles(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to the JD-R theory, the interaction between an individual's career calling and available job resources leads to the development of goal strategies aimed at achieving career value identity. Regulatory focus, a prominent framework for goal strategy, encapsulates the fundamental motivations of striving for growth or avoiding risks in career pursuits(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The process of behavioral decision-making following a career calling, which involves seeking meaning, varies according to specific regulatory focus pathways. Empirical evidence indicates that nurses with a promotion focus are more proficient at converting career-related pressures into opportunities for growth, exhibiting significantly higher levels of career satisfaction and innovative behaviors compared to those with a prevention focus(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). Promotion focus has been found to have a significant positive correlation with job crafting behaviors, while prevention focus is linked to adaptive crafting(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Moreover, longitudinal research utilizing two-year follow-up data suggests that a prevention focus attenuates the positive effects of job crafting on career growth, whereas a promotion focus enhances this relationship(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Consequently, regulatory focus serves as a crucial moderator in the context of job crafting.\u003c/p\u003e\u003cp\u003eIn conclusion, the process of job crafting among nurses is shaped by a multitude of factors; however, existing research predominantly examines the independent impact of individual factors and lacks a comprehensive analysis of the synergistic effects of multiple factors. Consequently, this study aims to address the following three core questions from an integrative perspective: What are the characteristics of the current level of job crafting within the nursing population, and are there differences across groups? What factors influence nurses' job crafting? Are there interactions among these various influencing factors? This study proposes to employ a three-dimensional analytical framework (status quo-motivators-mechanisms) to overcome the limitations of single-factor research, provide a scientific foundation for nursing managers to develop systematic intervention strategies, and simultaneously advance the theoretical understanding of job crafting within healthcare contexts.\u003c/p\u003e"},{"header":"3. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e3.1. Aims\u003c/h2\u003e\u003cp\u003eTo investigate the factors influencing job crafting levels among clinical nurses and elucidate the internal mechanisms linking personality traits to job crafting.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e3.2. Study Design and Participants\u003c/h2\u003e\u003cp\u003eA multicenter cross-sectional study was conducted from February to March 2025 in Inner Mongolia, China. The sample size was determined using the standard formula for cross-sectional studies: \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u003cem\u003eZ\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026times;\u003cem\u003ep\u003c/em\u003e\u0026times;(1\u0026thinsp;\u0026minus;\u0026thinsp;\u003cem\u003ep\u003c/em\u003e)/\u003cem\u003ee\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e, where \u003cem\u003eZ\u003c/em\u003e represents the Z-score corresponding to the desired confidence level (commonly 1.96 for a 95% confidence interval), \u003cem\u003ep\u003c/em\u003e denotes the anticipated proportion (set at 0.5 to ensure the maximum sample size), and \u003cem\u003ee\u003c/em\u003e signifies the allowable margin of error (typically 5%, or 0.05). Substituting these values into the formula yields an initial sample size of approximately 384. To account for the design effect associated with cluster sampling, the sample size is typically increased by a factor of 1.5 to 2, resulting in an adjusted sample size range of 576 to 768.\u003c/p\u003e\u003cp\u003eThis study employed a three-stage stratified sampling method. Initially, six league cities/prefecture-level cities were stratified based on the regional divisions of the Inner Mongolia into eastern, central, and western regions. Subsequently, 12 tertiary-level hospitals were stratified according to the distribution of regional tertiary-level hospitals. Finally, within the selected hospitals, nurses were chosen using a cluster sampling method, stratified by hospital size (number of beds) and department type. A detailed description of the sampling method is provided in Supplementary File 1. Ultimately, 1,273 nurses were selected. The inclusion criteria were: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) registered nurses with a valid nursing practice certificate; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) a minimum of one year of clinical work experience; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) informed consent and voluntary participation. The exclusion criteria were: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) registered nurses undergoing training, further education, or internships; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) absence from work during the survey period due to reasons such as vacation, study leave, illness, or childbirth; and (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) inability to complete the survey, such as experiencing a major life event. This cross-sectional study was conducted in accordance with the STROBE guidelines. The completed checklist is provided as supplementary material (STROBE-checklist-v4-cross-sectional.pdf).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e3.3. Data Collection\u003c/h2\u003e\u003cp\u003eThis study utilized the web-based platform Questionnaire Star (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.wjx.cn/\u003c/span\u003e\u003cspan address=\"https://www.wjx.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) for data collection, ensuring data validity and reliability through rigorous quality control measures. During the questionnaire design phase, the initial version was developed and refined based on a comprehensive literature review and expert consultation. In the distribution and retrieval phase, measures were implemented to enhance data integrity, including restricting submissions to a single device IP, binding responses to WeChat IDs to prevent duplicates, and imposing a minimum submission duration of 90 seconds to deter rapid response behaviors. During the data processing phase, invalid data, such as mechanical responses, logical inconsistencies, attention errors, and excessive missing values, were systematically excluded. Ultimately, 1,446 questionnaires were collected, and after thorough screening, 1,273 valid questionnaires were retained, resulting in an effective response rate of 88.04%.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e3.4. Instruments\u003c/h2\u003e\u003cp\u003e3.4.1. Demographic and Sociological Factors: Following an extensive review of the literature, the research team developed and administered a comprehensive general information questionnaire. This questionnaire encompassed various variables, including department type, ethnicity, age, gender, education level, marital status, professional title, job position, night shifts per month, total years of work experience, employment status, self-perceived health status, and frequency of off-site training per year.\u003c/p\u003e\u003cp\u003e3.4.2. Job Crafting Scale: This scale is a multidimensional assessment tool originally developed by Dvorak's team(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) and subsequently adapted for cross-cultural contexts by Zhu Shixiao's team(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). It comprises three sub-dimensions: relational crafting, task crafting, and cognitive crafting, with a total of 21 items. Responses are measured on a 5-point Likert scale (1\u0026thinsp;=\u0026thinsp;strongly disagree, 5\u0026thinsp;=\u0026thinsp;strongly agree), with the aggregate score indicating the individual's level of job crafting. The original scale demonstrated an internal consistency coefficient of 0.910, which was enhanced to 0.978 in the present study, with a Guttman split-half coefficient of 0.922.\u003c/p\u003e\u003cp\u003e3.4.3. The Career Calling Scale: This scale derived from Dobrow's theoretical framework(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e), has been adapted into Chinese by Pei Yujing and colleagues(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). This 12-item instrument employs a 5-point Likert scale, featuring representative items such as \"I am willing to make sacrifices for my current job.\" The original scale demonstrated a reliability coefficient of 0.940, while the current study reported a Cronbach's α of 0.976 and a Guttman split-half coefficient of 0.963, indicating a high level of reliability.\u003c/p\u003e\u003cp\u003e3.4.4. Nurse Regulatory Focus Scale (NRFQ): NRFQ was originally developed by Wallace(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e) and subsequently localized and validated by Li Shuying's team(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). This scale is structured into two dimensions: promotion focus and prevention focus. It comprises 12 items, each rated on a 5-point Likert scale, yielding a total score range of 12 to 60. In the present study, the scale demonstrated high internal consistency, with a Cronbach's alpha of 0.973 and a Guttman split-half coefficient of 0.952. These metrics indicate the scale's efficacy in distinguishing the behavioral characteristics of caregivers with varying regulatory focus orientations.\u003c/p\u003e\u003cp\u003e3.4.5. The Psychological Capital Questionnaire: The Chinese version of Luthans' classic scale(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e) was validated for applicability to nursing groups by Luo Hong's team(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). This instrument encompasses 20 items across four dimensions: self-efficacy, hope, resilience, and optimism, and is rated on a 6-point scale. The overall reliability of the scale was 0.923, with subscale alpha coefficients ranging from 0.718 to 0.890, and a test-retest reliability of 0.819. In this study, the Cronbach's alpha was found to be 0.989 and a Guttman split-half coefficient of 0.977, indicating excellent reliability.\u003c/p\u003e\u003cp\u003e3.4.6. Ten-Item Personality Inventory in China (TIPI-C): This scale was developed following the methodology established by Gosling(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). This inventory, validated by Li Jinde(\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e), utilizes a 10-item condensed version of the personality assessment tool to evaluate dimensions such as extraversion, agreeableness, conscientiousness, emotional stability, and openness, using a 7-point scale (1\u0026thinsp;=\u0026thinsp;absolute disagreement, 7\u0026thinsp;=\u0026thinsp;absolute agreement). Items 1, 3, 5, 7, and 9 are scored positively, while the remaining items are scored negatively. Each personality dimension is represented by a specific combination of items; for example, extraversion is assessed using items 1 and 6. The Cronbach's α for this inventory was measured as 0.855 and a Guttman split-half coefficient of 0.882.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.5. Data Analysis\u003c/h2\u003e\u003cp\u003eData organization was conducted using Microsoft Excel 2019, while statistical analyses were performed using SPSS Statistics version 24.0. Categorical variables were presented as frequency (n) and composition ratio (%). The normality of continuous variables was assessed using the Kolmogorov-Smirnov test. Variables following a normal distribution were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (M\u0026thinsp;\u0026plusmn;\u0026thinsp;SD), whereas non-normally distributed data were represented by the median and interquartile range (M[Q1, Q3]). For continuous variables adhering to a normal distribution, analyses were conducted using the independent samples t-test for two groups or one-way analysis of variance (ANOVA) for multiple groups. Pearson's correlation coefficient was employed for bivariate normally distributed data, while Spearman's rank correlation coefficient was utilized for non-normally distributed data. Multiple linear regression models were developed to address multicollinearity, ensuring a variance inflation factor (VIF) of less than 5, and stepwise regression was applied for variable selection. Mediation effect analysis was conducted using the Bootstrap method with 5000 resamples, facilitated by the Hayes PROCESS macro program (Models 4 and 6).\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e4.1. Descriptive and Univariate Analysis\u003c/h2\u003e\u003cp\u003eA total of 1,273 nurses participated in the study, ranging in age from 21 to 59 years, with a mean age of 34.81 years (SD\u0026thinsp;=\u0026thinsp;7.12). Of these, 371 (29.1%) were internal medicine nurses, 272 (21.4%) were surgical nurses, 152 (11.9%) were obstetrics and gynecology nurses, 55 (4.3%) were pediatric nurses, 184 (14.5%) were employed in emergency, critical care, and intensive care unit, and 239 (18.8%) were from other departments. The study's findings indicated that factors such as gender, department, education level, professional title, job position, night shifts per month, total years of work experience, self-perceived health status, and frequency of off-site training per year significantly influenced clinical nurses' job crafting. As demonstrated in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, all observed differences were statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003ePost hoc multiple comparisons revealed that nurses with an associate degree or below exhibited significantly higher levels of job crafting compared to those with a bachelor's degree; job crafting was significantly higher among nurses with primary and senior titles compared to those with intermediate titles; job crafting was significantly more prevalent among nurses who worked\u0026thinsp;\u0026le;\u0026thinsp;4 night shifts per month compared to those working 5ཞ9 shifts per month; nurses with \u0026lt;\u0026thinsp;3 years of professional experience exhibited higher levels of job crafting than those with 6ཞ10 years or \u0026gt;\u0026thinsp;10 years of experience; nurses who perceived themselves as having better health reported higher levels of job crafting; the frequency of training also played a role; nurses who participated in training twice a year demonstrated significantly higher job crafting than those who attended training once a year, refer to Supplementary File 2.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSingle factor analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003en\u003c/em\u003e(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eJob crafting(score, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003et/F\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65(5.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86.48\u0026thinsp;\u0026plusmn;\u0026thinsp;18.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e3.543\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1208(94.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.27\u0026thinsp;\u0026plusmn;\u0026thinsp;16.91\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eDepartment\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInternal medicine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e371(29.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.75\u0026thinsp;\u0026plusmn;\u0026thinsp;16.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e3.307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e272(21.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80.25\u0026thinsp;\u0026plusmn;\u0026thinsp;17.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObstetrics and gynecology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e152(11.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80.52\u0026thinsp;\u0026plusmn;\u0026thinsp;16.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePediatrics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e55(4.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.49\u0026thinsp;\u0026plusmn;\u0026thinsp;15.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmergency, critical care, and intensive care unit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e184(14.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.21\u0026thinsp;\u0026plusmn;\u0026thinsp;16.51\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther departments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e239(18.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.79\u0026thinsp;\u0026plusmn;\u0026thinsp;17.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eEthnicity\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHan Chinese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1037(81.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.86\u0026thinsp;\u0026plusmn;\u0026thinsp;16.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e1.404\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.240\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMongolian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e182(14.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.19\u0026thinsp;\u0026plusmn;\u0026thinsp;16.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHui Chinese\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18(1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83.33\u0026thinsp;\u0026plusmn;\u0026thinsp;17.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOther ethnic groups\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36(2.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74.08\u0026thinsp;\u0026plusmn;\u0026thinsp;22.65\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eEducation level\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAssociate degree or below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e143(11.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.65\u0026thinsp;\u0026plusmn;\u0026thinsp;18.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e7.019\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBachelor's degree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1119(87.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.07\u0026thinsp;\u0026plusmn;\u0026thinsp;16.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaster's degree or above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11(0.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e89.91\u0026thinsp;\u0026plusmn;\u0026thinsp;12.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnmarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e299(23.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80.07\u0026thinsp;\u0026plusmn;\u0026thinsp;19.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e2.569\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.077\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried without children\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e164(12.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80.21\u0026thinsp;\u0026plusmn;\u0026thinsp;16.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried with children\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e810(63.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.87\u0026thinsp;\u0026plusmn;\u0026thinsp;16.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eProfessional title\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e545(42.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80.58\u0026thinsp;\u0026plusmn;\u0026thinsp;18.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e8.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntermediate-level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e499(39.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.38\u0026thinsp;\u0026plusmn;\u0026thinsp;16.66\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSenior-level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e229(18.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.21\u0026thinsp;\u0026plusmn;\u0026thinsp;13.42\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eJob position\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNurse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1183(92.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.42\u0026thinsp;\u0026plusmn;\u0026thinsp;17.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e-2.482\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHead Nurse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90(7.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.23\u0026thinsp;\u0026plusmn;\u0026thinsp;13.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eNight shifts per month\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;4 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e479(37.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80.29\u0026thinsp;\u0026plusmn;\u0026thinsp;15.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e3.639\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5ཞ9 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e665(52.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.54\u0026thinsp;\u0026plusmn;\u0026thinsp;17.26\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;9 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e129(10.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.65\u0026thinsp;\u0026plusmn;\u0026thinsp;19.62\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eTotal years of work experience\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;3 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e174(13.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.75\u0026thinsp;\u0026plusmn;\u0026thinsp;17.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e5.575\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3ཞ5 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e119(9.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81.39\u0026thinsp;\u0026plusmn;\u0026thinsp;17.99\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6ཞ10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e291(22.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.75\u0026thinsp;\u0026plusmn;\u0026thinsp;18.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e689(54.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.59\u0026thinsp;\u0026plusmn;\u0026thinsp;15.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eEmployment status\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-established Position\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e942(74.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.97\u0026thinsp;\u0026plusmn;\u0026thinsp;17.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e1.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.316\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEstablished Position\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e331(26.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.88\u0026thinsp;\u0026plusmn;\u0026thinsp;16.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eSelf-perceived health status\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExcellent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e525(41.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86.26\u0026thinsp;\u0026plusmn;\u0026thinsp;17.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e74.444\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVery good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e349(27.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.53\u0026thinsp;\u0026plusmn;\u0026thinsp;14.22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e327(25.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e71.43\u0026thinsp;\u0026plusmn;\u0026thinsp;13.64\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64(5.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64.23\u0026thinsp;\u0026plusmn;\u0026thinsp;14.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8(0.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.5\u0026thinsp;\u0026plusmn;\u0026thinsp;14.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eFrequency of off-site training per year\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1145(89.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.29\u0026thinsp;\u0026plusmn;\u0026thinsp;17.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e3.522\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e68(5.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85.16\u0026thinsp;\u0026plusmn;\u0026thinsp;12.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15(1.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.73\u0026thinsp;\u0026plusmn;\u0026thinsp;23.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4 times or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45(3.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e79.33\u0026thinsp;\u0026plusmn;\u0026thinsp;18.28\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e4.2. Analysis of the Current Status of Job Crafting Among Nurses\u003c/h2\u003e\u003cp\u003eAs indicated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the extent of job crafting among clinical nurses was moderate. A one-sample t-test analysis revealed that the mean scores for job crafting, career calling, regulatory focus, psychological capital, and the five personality traits were significantly above the theoretical median. These findings suggest that the nursing cohort possesses a more favorable self-assessment regarding their occupational psychological resources, such as psychological capital and regulatory focus, as well as their personality traits.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAnalysis of the current situation\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTest Statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTask crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e3.51\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e18.884\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCognitive crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e3.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e35.972\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRelational crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e3.88\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e38.931\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJob crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e3.75\u0026thinsp;\u0026plusmn;\u0026thinsp;0.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.785\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCareer calling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e3.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e34.823\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePromotion focus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e57.418\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrevention focus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e50.225\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegulatory focus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e55.030\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSelf-Efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.86\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51.368\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHope\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.83\u0026thinsp;\u0026plusmn;\u0026thinsp;0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e50.141\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eResilience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.85\u0026thinsp;\u0026plusmn;\u0026thinsp;0.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51.121\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOptimism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.81\u0026thinsp;\u0026plusmn;\u0026thinsp;1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e44.609\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePsychological capital\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e51.456\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExtraversion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e32.287\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAgreeableness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.52\u0026thinsp;\u0026plusmn;\u0026thinsp;1.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e14.467\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConscientiousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.75\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e22.697\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEmotional stability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.82\u0026thinsp;\u0026plusmn;\u0026thinsp;1.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e24.791\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOpenness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e5.04\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e33.207\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTIPI-C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e4.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e28.745\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: *** represents \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001. On the Likert 5 scale, a score of 3 represents neutrality, so the test value is 3; on the Likert 6 scale, a score of 3.5 represents neutrality, so the test value is 3.5; and on the Likert 7 scale, a score of 4 represents neutrality, so the test value is 4.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.3. Pearson Correlation Analysis\u003c/h2\u003e\u003cp\u003eThe Pearson correlation analysis results indicated that career calling, regulatory focus, psychological capital, and TIPI-C were all positively correlated with job crafting (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.797, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01;\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.766, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01༛\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.772, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01; \u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.539, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01), as detailed in Supplementary File 3.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.4. Linear Regression Analysis\u003c/h2\u003e\u003cp\u003eWe performed linear regression analyses using variables that demonstrated statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the univariate analyses, including career calling, each of the TIPI-C dimensions, and nurse regulatory focus as independent variables, with nurse job crafting as the dependent variable. For categorical variables related to general information, dummy variables were assigned as described in Supplementary File 4.\u003c/p\u003e\u003cp\u003eThe regression analysis results revealed a good model fit, with an adjusted \u003cem\u003eR\u003c/em\u003e-squared value of 0.689. This indicates that the independent variables in the regression model account for 68.9% of the variance in the dependent variable, suggesting that the current model effectively identifies the factors influencing job crafting.\u003c/p\u003e\u003cp\u003eThe findings indicated that several factors significantly influenced nurses' job crafting, including career calling, extraversion, agreeableness, conscientiousness, regulatory focus, department, educational level, self-perceived health, and gender. Specifically, nurses working in surgical, obstetrics and gynecology, and pediatrics departments exhibited significantly higher levels of job crafting compared to their counterparts in other departments. Additionally, nurses holding a master's degree or higher demonstrated significantly greater job crafting than those with an associate degree or below. Conversely, nurses with very poor health engaged in significantly less job crafting compared to those with good health. Furthermore, female nurses exhibited significantly lower levels of job crafting than their male counterparts (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eLinear regression analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnstandardized Coefficients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStandardized Coefficients\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003et-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eVIF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e(constant)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.905\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.432\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eDepartment\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInternal medicine\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.420\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.503\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.615\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.988\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSurgery\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.962\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.047\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.214\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.819\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObstetrics and gynecology\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.893\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.767\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.585\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePediatrics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.043\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.223\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmergency, critical care, and intensive care unit\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.645\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.648\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.517\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.693\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther departments\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eEducation level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBachelor's degree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.982\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.222\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMaster's degree or above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.034\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.976\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.159\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssociate degree or below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eProfessional title\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIntermediate-level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.311\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.756\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.079\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.832\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSenior-level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.028\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003eNight shifts per month\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5ཞ9 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.225\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.733\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.496\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;9 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.959\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.944\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.345\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.295\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;4 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eTotal years of work experience\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3ཞ5 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.047\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.902\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.367\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.574\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6ཞ10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.362\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.717\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.504\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026gt;10 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.836\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.823\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.411\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.532\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;3 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003eSelf-perceived health status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVery good\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.327\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.893\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.059\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.349\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGood\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.891\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.251\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.584\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFair\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.811\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.276\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-8.280\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.324\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.094\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExcellent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003eFrequency of off-site training per year\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.736\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.355\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.176\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.145\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.457\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.648\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.058\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 times or more\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.674\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.007\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.455\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.649\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.031\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 times\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.984\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.038\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.337\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.090\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eJob position\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHead nurse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.697\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.573\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.566\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.339\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNurse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eCareer calling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.741\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.444\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.360\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4.429\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eExtraversion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.514\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.616\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.998\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAgreeableness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.567\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.811\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.005\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.693\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eConscientiousness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.440\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.060\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-2.048\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.502\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eEmotional stability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.260\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.240\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.215\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.363\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eOpenness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.998\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.981\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNurse regulatory focus\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.304\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.714\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eAdjusted R-squared\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003e0.683\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eF\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003e92.538\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: The dependent variable was job crafting. Due to the strong covariance observed between the dimensions of nurses' regulatory focus (promotion focus and prevention focus), psychological capital, and their respective dimensions, these variables were excluded from the linear regression analysis as independent variables to ensure the accuracy of the results.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e4.5. Mediating Effect Analysis\u003c/h2\u003e\u003cp\u003eTo further investigate the potential interaction effect between various influences and job crafting, this study employed path analysis. The findings from the double-chain mediation model revealed that the overall impact of extraversion and conscientiousness on job crafting was significant(\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.305, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.074, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting that higher levels of extraversion and conscientiousness are associated with more robust job crafting behaviors. Even after controlling for mediating variables, extraversion and conscientiousness continued to exert a significant positive effect on job crafting(\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.856, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001; \u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.420, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), albeit with a reduced effect size, indicating partial mediation. The model fit was strong, with the regression models for career calling, regulatory focus, and job crafting yielding \u003cem\u003eR\u0026sup2;\u003c/em\u003e values of 0.419/0.213, 0.716/0.714, and 0.673/0.668, respectively. Bootstrap analysis with 5000 iterations confirmed the robustness of the results, as all confidence intervals for indirect effects excluded zero. Career calling emerged as the primary mediator, with its individual mediating effects (Ind1) accounting for 49.81% and 54.64% of the total indirect effects, respectively. This indicates that extraversion and conscientiousness primarily enhance job crafting through the enhancement of career calling. The chain mediation effect (Ind3) was significant, indicating that extroversion and conscientiousness influenced moderating focus via career calling, which subsequently impacted job crafting. This accounted for 26.38% and 28.83% of the total indirect effect, respectively. Although the independent mediating effect of moderating focus was relatively weak, contributing only 3.92% and 2.86% for Ind2, it served a complementary function within the chain pathway. The mediating effect of career calling was considerably stronger than the independent mediation effect of moderating focus. Furthermore, the direct effect of career calling was more pronounced than its chained effect through moderating focus, and the chained mediation effect was significantly more robust than the independent mediation of moderating focus (refer to Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea and \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb).\u003c/p\u003e\u003cp\u003eAccording to the analysis of a simple mediation model, the total effect of agreeableness on job crafting was found to be significant (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.117, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting that increased agreeableness is associated with enhanced job crafting behavior. Even after accounting for mediating variables, agreeableness continued to exert a significant positive influence on job crafting (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.223, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), although the effect size was diminished, indicating the presence of partial mediation. The mediating effect was quantified at 1.894, representing 60.77% of the total effect. The model fit was demonstrated by the regression models for moderating focus and job crafting, which exhibited \u003cem\u003eR\u0026sup2;\u003c/em\u003e values of 0.170 and 0.615, respectively, indicating strong explanatory power. Bootstrap analysis with 5000 iterations revealed that the confidence intervals for all indirect effects did not include zero, confirming the robustness of the findings (refer to Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;2).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePath diagram\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEffect\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBootSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBootLLCI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBootULCI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eEffect Proportion\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003ePath 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.449\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.132\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.749\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e80.11%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd1: extraversion -\u0026gt;career calling -\u0026gt;job crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.145\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.168\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.810\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e49.81%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd2: extraversion -\u0026gt;regulatory focus -\u0026gt;job crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.169\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.058\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.061\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.288\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.92%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd3: extraversion -\u0026gt;career calling -\u0026gt;regulatory focus-\u0026gt;job crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.865\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.409\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e26.38%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd1- Ind2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.976\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.339\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd1- Ind3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.269\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.461\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.530\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd2- Ind3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.967\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.258\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.709\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e\u003cp\u003ePath 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.166\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.329\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.979\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e86.33%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd1: conscientiousness -\u0026gt;career calling -\u0026gt;job crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.679\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.141\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.412\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.962\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e54.64%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd2: conscientiousness -\u0026gt;regulatory focus-\u0026gt;job crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.088\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.179\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.86%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd3: conscientiousness -\u0026gt;career calling -\u0026gt;regulatory focus -\u0026gt;job crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.886\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.676\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.113\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e28.83%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd1- Ind2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.591\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.302\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.893\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd1- Ind3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.793\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.201\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.387\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.178\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eInd2- Ind3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.798\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.109\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-1.027\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-0.595\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026ndash;\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePath 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eagreeableness -\u0026gt;regulatory focus -\u0026gt;job crafting\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.894\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.1344\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.6217\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.1579\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e60.77%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"5. Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003e5.1. Analysis of the Current Status of Nurses' Job crafting and Group Differences\u003c/h2\u003e\u003cp\u003eThis study determined that the extent of job crafting among clinical nurses was moderately high, aligning with the findings of Park(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). The average age of the nurses was 34.81 years (SD\u0026thinsp;=\u0026thinsp;7.12), indicating a relatively youthful nursing workforce in Inner Mongolia, China. This age distribution may influence the patterns of job crafting differently. Younger nurses demonstrated a greater propensity to meet professional demands through task crafting, whereas older nurses tended to focus on relational crafting. This observation is consistent with Zhang's research(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) on age stratification among nursing staff. Furthermore, the level of task crafting was notably higher among nurses with less than three years of experience compared to other groups. This finding supports Benner's theory of novice development, which suggests that new nurses develop clinical competence by actively adapting their work styles during the process of occupational socialization(\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). The level of job crafting significantly declined among individuals in the 6ཞ10 years experience group, indicating a heightened risk of burnout at this career stage and underscoring the necessity to avoid the \"mid-career trap.\" This observation aligns with the U-shaped distribution of professional title: nurses with primary title exhibited greater motivation for crafting, driven by the need for career exploration; those with senior title often engaged in clinical teaching and systemic change initiatives, leveraging their professional authority; whereas nurses with intermediate title experienced role overload due to the demands of developing their specialties, leading to diminished motivation for crafting(\u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFurthermore, nurses working low-frequency night shifts (\u0026le;\u0026thinsp;4 times per month) demonstrated significantly higher levels of job crafting compared to those in the high-frequency group (5ཞ9 times). This suggests that frequent disruptions to circadian rhythms may inhibit proactive change behaviors by depleting psychological resources. This finding corroborates the research of Van(\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e) on the cognitive load experienced by shift-based nursing staff. The findings indicate that the impact of continuing education exhibits a nonlinear characteristic, with the biannual out-of-home training cohort demonstrating superior performance. This suggests that a moderate frequency of training, when combined with high-quality content, is more effective in enhancing occupational adaptability than merely increasing the frequency of training sessions. Zhuang's study(\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e) corroborates this by indicating that training frequency surpassing a certain threshold may induce learning fatigue, thereby diminishing the effectiveness of knowledge translation. Collectively, these findings suggest that job crafting within a young, highly mobile nursing workforce results from the dynamic interplay between individual attributes and the organizational environment. Future research should focus on examining the moderating effects of contextual factors, such as department type, to refine the implementation strategies for career development interventions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003e5.2. Analysis of Factors Influencing Nurses' Job Crafting\u003c/h2\u003e\u003cp\u003eIn alignment with the JD-R theory proposed by Shan(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e), the data from this study indicate that nurses' job crafting behaviors are systematically influenced by both environmental resources (such as the departments) and individual resources (including gender, education, perceived health, personality traits, career calling, and regulatory focus). At the environmental level, surgical nurses have notably enhanced work efficiency through task integration, corroborating Jakobsson's(\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e) conclusions regarding adaptive strategies in high-stress units. In contrast, obstetrics and gynecology nurses are required to develop communication patterns that emphasize the agreeableness of personality, tailored to the unique characteristics of the population they serve. Interestingly, the occurrence of innovative behaviors among pediatric nurses was significantly higher than typically anticipated, contradicting Zelesniack's(\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e) assertion that due conscientiousness inhibits innovation. This discrepancy may be attributed to the special needs of pediatric patients, which could potentially diminish the impact of professional normative constraints. These findings indicate that clinical managers should implement tailored training programs that reflect the cultural characteristics of their respective departments. For instance, intensive multitasking coordination training could be beneficial in surgical settings, empathy communication workshops may enhance interactions in obstetrics and gynecology, and the introduction of fault-tolerance mechanisms could foster innovative practices in pediatrics.\u003c/p\u003e\u003cp\u003eAt the individual level, this study elucidated the structural differentiation mechanism of gender and education on nurses' job crafting. The findings indicated that female nurses encountered cognitive resource allocation dilemmas due to role conflicts between family and profession, aligning with the theory of occupational gender role solidification(\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). In contrast, male nurses proactively constructed their professional identities by competing for technical positions, a strategic approach consistent with the findings of Younas(\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). The educational level exhibited a U-shaped distribution in relation to job crafting behaviors, nurses with a master's degree or higher demonstrated a strong propensity to reinvent themselves based on their professional strengths, aiming for higher career achievements(\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). Conversely, nurses with an associate degree or below engaged in practical crafting behaviors, driven by accumulated experience and the pressure of challenges(\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Nurses with a bachelor's degree experienced a crafting trough, closely associated with career development bottlenecks, insufficient resource support, and deficiencies in the accreditation system; male nurses actively shape their professional identity through competition for technical positions, highlighting deficiencies in system articulation(\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). Further studies have demonstrated that career satisfaction and the work environment moderate crafting behaviors, with nurses holding bachelor's degrees being more susceptible to burnout in unsupportive settings(\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e). These findings indicate the necessity for nursing management to develop a gender-sensitive support network to alleviate role conflicts experienced by female nurses. Additionally, there is a need to innovate the specialty certification system for bachelor's degree nurses to enhance their career vitality through career path reconstruction.\u003c/p\u003e\u003cp\u003eAt the individual level, career calling significantly and positively predicts nurses' job crafting levels, suggesting that nurses with a strong sense of career calling are more likely to proactively adjust their job content and roles. This observation aligns with the findings of Esteves(\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e). In a comprehensive examination of the mechanisms underlying these phenomena, Solms(\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e) identified that nurses develop psychological resilience through goal-oriented behaviors, such as proactive resource acquisition, which serve to effectively mitigate occupational stress. In the present study, it is suggested that nurses with a strong career calling may engage in job crafting via a similar mechanism. A pronounced sense of career calling not only augments nurses' career satisfaction but also diminishes burnout and turnover intentions. Empirical evidence indicates a robust correlation between a sense of career calling and nurses' job satisfaction, organizational commitment, and career development(\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). Furthermore, a sense of professional mission can bolster nurses' career success by enhancing their psychological resilience(\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e). Within the context of nursing management, promoting nurses' sense of professional mission and psychological resilience is a crucial strategy for increasing career satisfaction and reducing turnover intentions(\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). Consequently, nursing managers should prioritize providing nurses with career development opportunities and support to strengthen their sense of professional mission and psychological resilience, thereby improving the overall quality of care and the ability of nurses to transform their work.\u003c/p\u003e\u003cp\u003eAt the individual level, regulatory focus is a significant and positive predictor of nurses' job crafting, indicating that nurses' personal regulatory tendencies influence how they redefine their roles. This finding is corroborated by Roczniewska's study(\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e). Considering the highly dynamic nature of the nursing profession and the diverse needs of patients(\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e), regulatory focus suggests that nurses with a promotion regulatory focus are inclined to pursue professional growth by exploring new responsibilities. In contrast, those with a prevention focus tend to avoid risks by optimizing existing processes, both of which contribute to job crafting(\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e). Notably, this study found that the promotion focus dimension scored higher than the prevention focus, which may be attributed to the nursing professional culture that emphasizes achievement-oriented behaviors. Consequently, nursing managers can enhance nurses' regulatory focus through tailored strategies by providing innovative task platforms for promotion focus nurses and establishing a risk warning support system for prevention focus nurses, thereby optimizing job crafting behaviors. Future investigations should also differentiate regulatory focus dimensions to provide a more precise basis for decision-making in nursing human resource management.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003e5.3. Analysis of the Mediating Effects of Nurse Job Crafting\u003c/h2\u003e\u003cp\u003e We were intrigued to discover interaction effects between personality traits and career calling, as well as regulatory focus and job crafting. The results suggest that the traits of extraversion and conscientiousness predominantly influence job crafting behaviors through career calling, accounting for a substantial contribution of 49.81\u0026ndash;54.64%, compared to a lesser contribution of 2.86\u0026ndash;3.92% from regulatory focus focus. This finding provides cross-situational validation with Bakker's study(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), which similarly demonstrates that career calling, as a fundamental intrinsic resource, possesses greater explanatory power in mitigating emotional depletion than regulatory focus. These disparities may be attributed to the contextual demands unique to the nursing profession(\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e), where exposure to patient distress and cues of life vulnerability serve as persistent contextual stimuli that activate the empathic response network in extroverted individuals and the responsibility perception system in conscientious individuals. In particular, extraverted nurses prioritize forming affective connections over pursuing instrumental goals when expanding their social support networks. In contrast, conscientious nurses' involvement in quality improvement practices is strongly linked to their professional mission, particularly through the achievement of nursing safety goals(\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). This specific alignment of traits, situations, and goals not only accounts for variations in behavioral performance across different contexts but also underscores the moderating role of autonomous decision-making space and immediate feedback mechanisms in enhancing trait efficacy within the nursing profession.\u003c/p\u003e\u003cp\u003eFurthermore, traits associated with agreeableness can substantially impact nurses' job crafting behaviors by regulatory focus mechanisms. Empirical evidence supports this assertion, highlighting the cooperative, empathetic, and altruistic dimensions of agreeableness(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e), which predispose highly agreeable nurses to pursue socially desirable objectives. This social orientation aligns naturally with the \"growth\" logic of promotion focus, prompting individuals to prioritize positive outcomes and thereby fostering proactive work crafting behaviors(\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e). This facilitation mechanism is particularly pronounced in teamwork settings, where consistent leadership in facilitation orientation not only reinforces team identity but also significantly enhances the innovation effectiveness of nursing teams through goal synergy(\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e). Nonetheless, it is crucial to acknowledge that the specific nature of nursing necessitates the concurrent fulfillment of therapeutic alliance building and medical risk aversion, resulting in the inevitable coexistence of prevention focus mechanisms(\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e). Neuroimaging evidence indicates that individuals with robust prefrontal-limbic system connectivity exhibit superior focus-switching abilities in resuscitation scenarios, providing a neuroplasticity-based explanation for the transformation of traits into behaviors(\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAccording to the JD-R theoretical framework, career calling and regulatory focus serve as key mediating variables in the relationship between personality traits and job crafting. The intrinsic mechanisms of these variables are demonstrated by the continuous activation of nurses' commitment to job crafting, facilitated by the dual motivational system of a sense of meaning and a sense of mission(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Concurrently, regulatory focus enhances the ability to identify opportunities through a success-oriented approach and optimizes risk decision-making by emphasizing the avoidance of failures [11]. Together, these factors create a synergistic closed-loop structure of \"motivational stimulation-cognitive regulation.\" Consequently, nursing managers can enhance nurses' ability to construct meaning through occupational value strengthening training and improve their situational adaptation strategies via cognitive flexibility training. This approach ultimately leads to the progressive enhancement of individual resource empowerment and the effectiveness of job crafting.\u003c/p\u003e\u003c/div\u003e"},{"header":"6. Limitations","content":"\u003cp\u003eThis study possesses several limitations that warrant consideration. Firstly, the cross-sectional design hinders the establishment of causal time-series relationships between variables, necessitating future longitudinal studies to verify the long-term effects of personality traits on job crafting. Secondly, the sample was restricted to tertiary hospitals in Inner Mongolia, potentially limiting the generalizability of the findings to primary healthcare institutions and diverse cultural contexts. Lastly, the analysis of mediating mechanisms did not account for environmental variables such as organizational support, which may lead to an underestimation of the moderating role of the management context. Consequently, future research should construct a multilevel interaction model.\u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eThe study indicated that the overall level of job crafting among clinical nurses was moderately high and was influenced by a variety of factors. At the individual level, variables such as gender, education level, self-perceived health status, personality traits, career calling, and regulatory focus significantly impacted job crafting performance. Environmentally, the job crafting abilities of nurses in the departments of surgery, obstetrics and gynecology, and pediatrics were notably higher compared to those in other departments. Among the personality traits, extraversion, agreeableness, and conscientiousness were strongly associated with job crafting. Further analysis demonstrated that extraversion and conscientiousness primarily facilitated job crafting behaviors through career calling, which played a predominant role in this process, while the moderating role of focus was limited. Additionally, agreeableness significantly influenced job crafting through the mechanism of moderating focus.\u003c/p\u003e\u003cp\u003eBased on these findings, it is advisable for nursing managers to implement the following strategies: optimize job allocation by thoroughly considering the alignment between individual personality traits and specific job demands; facilitate cross-departmental exchanges to enhance nurses' ability to engage in job crafting within high-pressure environments; and develop a framework for fostering a sense of career calling while monitoring health status dynamics to promote the integrated management of psychological resources and job demands.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 256px;\"\u003e\n \u003cp\u003eComplete designation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eAbbreviation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 256px;\"\u003e\n \u003cp\u003e1 World Health Organization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eWHO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 256px;\"\u003e\n \u003cp\u003e2\u0026nbsp;Job Demand-Resource Model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eJD-R\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 256px;\"\u003e\n \u003cp\u003e3 Nurse Regulatory Focus Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eNRFQ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 256px;\"\u003e\n \u003cp\u003e4 Ten-Item Personality Inventory in China\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eTIPI-C\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 256px;\"\u003e\n \u003cp\u003e5 one-way analysis of variance\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eANOVA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 256px;\"\u003e\n \u003cp\u003e6 variance inflation factor\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003eVIF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was performed in accordance with the Declaration of Helsinki. The studies involving human participants were reviewed and approved by the Ethics Committee of the Inner Mongolia People\u0026apos;s Hospital (202504004L). All participants gave informed consent and signed \u0026ldquo;yes\u0026rdquo; prior to data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest\u003cbr\u003e\u003c/strong\u003eThe authors declare no conflicts of interest. The funding agencies had no involvement in study design, data collection/analysis, manuscript preparation, or publication decisions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJW and YRL contributed\u0026thinsp;to\u0026thinsp;the\u0026thinsp;conceptualization\u0026thinsp;of\u0026thinsp;the\u0026thinsp;study, performed the analysis, wrote the manuscript; MS, YCH and PJT contributed significantly to investigation and project administration; YJC, YTW and \u0026nbsp;JXS \u0026nbsp; assisted with data curation; YLW and WZC contributed\u0026thinsp;to\u0026thinsp;the\u0026thinsp;conceptualization\u0026thinsp;of\u0026thinsp;the\u0026thinsp;study and reviewed the manuscript. All authors have read and approved the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJW: Master\u0026apos;s Candidate, Member of the Nursing Education Committee, Chinese Research Hospital Association, [email protected]\u003c/p\u003e\n\u003cp\u003eYRL: Deputy Director of Nursing Department, Member, International Nursing Branch, Asia-Pacific Vascular Academic Alliance, [email protected]\u003c/p\u003e\n\u003cp\u003eYLW: Director of Nursing, Member of the 28th Council of the Chinese Nursing Association, [email protected]\u003c/p\u003e\n\u003cp\u003eWZC: Chief Nurse Executive, Standing Committee Member, Nursing Education Committee, Chinese Research Hospital Association, [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was supported by the Science and Technology Program of the Joint Fund of Scientific Research for the Public Hospitals of Inner Mongolia Academy of Medical Sciences (2023GLLH0055), the Science and Technology Program of the Joint Fund of Scientific Research for the Public Hospitals of Inner Mongolia Academy of Medical Sciences (2023GLLH0084), and Ordos Key Research and Development Program Project (YF20240064).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe appreciate all nurses who took their time to participate in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTims M, Bakker AB, Derks D. 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Developmental Cognitive Neuroscience. 2023;60:101217.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Nurses, job crafting, career calling, TIPI-C, chain mediation","lastPublishedDoi":"10.21203/rs.3.rs-7156066/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7156066/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eJob crafting plays a pivotal role in nursing management, with its optimization having the potential to enhance the quality of clinical care, the efficacy of healthcare organizations, and the multifaceted professional development of nurses.\u003c/p\u003e\u003ch2\u003eDesign:\u003c/h2\u003e\u003cp\u003eA multi-center cross-sectional survey design was employed.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study utilized a sample of 1,273 clinical nurses from tertiary hospitals in Inner Mongolia, China, selected through multistage sampling. To analyze the influencing factors and pathways, multiple linear regression and the Hayes PROCESS macro program (Models 4 and 6) were employed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe findings indicated that clinical nurses exhibited a moderately high level of job crafting, which was significantly influenced by career calling, extraversion, agreeableness, conscientiousness, and regulatory focus; extraversion and conscientiousness operated through the chain mediation of career calling and regulatory focus; whereas agreeableness was mediated through a singular mediation pathway of regulatory focus. This finding elucidates the mechanism by which personality traits differentially influence occupational behavior.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe study identifies multiple factors affecting nurses' job crafting. It is imperative for nursing managers to comprehensively consider these factors and develop a targeted monitoring system to effectively enhance nurses' capacity for job crafting.\u003c/p\u003e\u003ch2\u003eClinical trial number:\u003c/h2\u003e\u003cp\u003enot applicable.\u003c/p\u003e","manuscriptTitle":"Influencing Factors and Mediating Mechanisms of Job Crafting in Clinical Nursing Practice","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-05 09:19:31","doi":"10.21203/rs.3.rs-7156066/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c6b9f559-378a-42e1-9520-e2d47c7f2908","owner":[],"postedDate":"August 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-23T05:08:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-05 09:19:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7156066","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7156066","identity":"rs-7156066","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}