Cross-cultural adaptation and psychometric evaluation of the Chinese version of the Sickness Presenteeism Scale- Nurses:A cross-sectional study

Cross-cultural adaptation and psychometric evaluation of the Chinese version of the Sickness Presenteeism Scale- Nurses:A cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cross-cultural adaptation and psychometric evaluation of the Chinese version of the Sickness Presenteeism Scale- Nurses:A cross-sectional study Chuang Li, Zhixing Meng, Youbei Lin, Lan Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4694732/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 07 May, 2025 Read the published version in BMC Nursing → Version 1 posted 13 You are reading this latest preprint version Abstract Background There is a lack of an evaluation instrument to gauge how presenteeism practices affect nurses' productivity at work and the quality of the medical treatment they provide. The purpose of this study was to translate the Sickness Presenteeism Scale-Nurse (SPS-N) into the Chinese version of the SPS-N and to verify its reliability and validity in Chinese nurses. Methods The SPS-N was translated according to the Brislin translation model after authorization by the original author. A convenience sampling method was used and the reliability and validity of the scale were tested among 503 Chinese nurses. Results The Cronbach's ɑ of the Chinese SPS-N was 0.924, and the content validity of the items ranged from 0.830 to 1.000. The four-factor exploratory factor model was used to explain 78.354% of the total variance. CMIN/DF = 2.527, RMSEA = 0.067, AGFI = 0.857, TLI = 0.941, IFI = 0.950 ,CFI = 0.949, GFI = 0.900, and PGFI = 0.692 were the model fit outcomes in the validation factor analysis. All of the model fit markers fell within reasonable bounds. Conclusion The reliability and validity of the Chinese version of the SPS-N can be used to evaluate the influence of nurses' presenteeism behavior on job performance. To inform nursing managers in developing programs and interventions to improve the performance of clinical nurses. nurses reliability validity presenteeism sickness Figures Figure 1 Figure 2 1 Background With the gradual improvement of the medical security system, the demand for high-quality services by patients is also increasing, and nurses have become important caregivers for patients and the main implementers of nursing operations[ 1 ].Nonetheless, presenteeism is quite widespread among nurses and is three to four times greater than in other industries because of shift work, a severe workload, job insecurity, a poor working environment, and other factors[ 2 , 3 ]. Presenteeism is the term used to describe the situation in which workers report for duty when ill and believe they should request sick time[ 4 ]. Nurses' presenteeism not only negatively impacts patients' physical and mental well-being but also lowers their standard of nursing care and interferes with patient treatment and rehabilitation[ 5 ]. In addition, there is a negative impact on nurses' job performance, motivation, satisfaction, and commitment to work[ 6 , 7 ]. Reduced competence means a loss of organizational productivity, which can ultimately result in serious financial losses[ 8 , 9 ]. According to reports of head nurses and nurses, the yearly economic losses resulting from presenteeism amount to 2.88 billion yuan and 4.38 billion yuan, respectively, in Henan Province according to scholars. Moreover[ 10 ], Letvak, a team of foreign scholars, conducted a study on nurses in the United States of North Carolina, and found that the annual per capita loss due to nurses' presenteeism behavior ranged from 1,346 to 9,000 US dollars[ 11 ]. Therefore, it is especially important to find suitable tools to evaluate the presenteeism behavior of nurses and reduce the negative impact of presenteeism. Currently, the tools used to evaluate presenteeism are the Stanford Presenteeism Scale[ 12 ], Endicott Work Productivity Scale[ 13 ], Health and Work Questionnaire [ 14 ] and the Luo Lu version of the presenteeism scale[ 15 ]. The above four assessment tools are applicable to the general occupational group and do not involve the transformation and measurement of productivity loss[ 16 ]. Furthermore, the Nurses Work Functioning Questionnaire (NWFQ) and Nurse Presenteeism Questionnaire (NPQ) can also be used to evaluate presenteeism. However, the NWFQ is concerned with the impairment of work function caused by common mental disorders[ 17 ], the NPQ assesses whether nurses report working when they have different health issues[ 18 ].Although the NWFQ and NPQ are tools developed for evaluating nurses, neither can be used effectively to access the effect of presenteeism on nurses' productivity and work output. Due to the lack of an evaluation instrument to gauge how presenteeism practices affect nurses' productivity at work and the quality of the medical treatment they provide, in 2023, the Turkish scholar Visser Karani Baris successfully developed the Sickness Presenteeism Scale-Nurse(SPS-N)[ 19 ].The SPS-N is a clinical tool based on evaluating nurses' general performance, patient safety, team relationships and emotions. Additionally, a four-factor framework that bridges the gap between single-dimensional measurement methods and the scale offers a thorough and reliable evaluation of nurses' presenteeism from a variety of levels and viewpoints[ 20 ].The SPS-N was translated into Chinese for this study, and in light of the significant prevalence of presenteeism among nurses, its validity and reliability were confirmed among Chinese clinical nurses. 2 Methods 2.1 Participants In 2023, from October 1 to February, a cross-sectional study was conducted. A convenience sampling method was used to select clinical nurses from the First Hospital of Jinzhou Medical University in Liaoning Province. Criteria for inclusion:①Licensed Nurse Practitioner with at least 6 months of experience as a hospital nurse.②Voluntary participation in research on this topic. Criteria for exclusion:①Nurses who left their clinical posts due to study abroad, vacation, maternity leave and other reasons during the investigation.②No nurses working with illness in the last month.③Nurses in internships or advanced training at the surveyed hospitals. Estimate the sample size based on Kendall's estimation method at 5-10 times the number of questionnaire entries, taking into account a sample attrition rate of 10 to 20% , preliminary calculations of the sample size for this study ranged from 116 to 252 cases, Meanwhile, in order to meet the requirements of sample data of not less than 100 cases in exploratory factor analysis (EFA) and sample size of at least 200 cases in validation factor analysis (CFA)[21]. Ultimately, the plan is to recruit 550 study participants. 2.2 Translation and Cross-cultural adaptation In this study, the original author was contacted by email for authorization, and then the SPS-N scale was translated into Chinese version according to Brislin translation model[22]: The SPS-N was developed by the team of Professor Veysel Karani Baris based on a multidisciplinary theory, including work performance (items 1-4), patient safety (items 6-12), team relationship (items 13-15) and emotion (items 16-21), a total of 21 items, using the Likert 5-level scoring method, with responses ranging from 1 "strongly disagree" to 5 "strongly agree". The total score is 21-105, with higher scores indicating higher sickness presenteeism among nurses. The original scale has good reliability and validity, and it tested the reliability and validity of 619 nurses living in 55 different cities in Turkey. The total Cronbach's α value was calculated as 0.928, the Cronbach's α value of the sub-dimension was calculated as 0.815~0.903, and the composite reliability value was calculated as 0.804~0.903[19]. -Step 1- The English version of the SPS-N was independently translated into the Chinese versions S1 and S2 by two students pursuing graduate nursing education and were native Chinese speakers with English proficiency up to level 6. The first author integrated the Chinese version of the scales S1 and S2, and fully discussed and modified them to form the Chinese version of the scale S. -Step 2- The Chinese version of Scale S was independently back-translated by a Doctor of Nursing Science and a Master's Degree in English (Medical English direction) who had never been in contact with the initial scale, resulting in the English versions of Scale SS1 and SS2. -Step 3- A professor in nursing management and an associate professor in clinical nursing integrate the back-translated version so that the semantic consistency rate reaches more than 95% to form the Chinese version to form the back-translated version of SS. -Step 4- According to the cultural adaptation guidelines, a total of six experts were invited to conduct two rounds of evaluation of the Chinese version of the SPS-N by e-mail and on-site consultation，achieving a balance between idiom conceptual equivalency and cultural adaptation in order to align language expressions with continental linguistic norms. 2.3 Measurement and instruments After reviewing the literature, the researcher designed a questionnaire to investigate the general demographic data of nurses, including: gender, age, department, working years, marriage and childbirth, etc. Chinese version of the Sickness Presenteeism Scale-Nurse, including 21 items in four dimensions: general performance (items 1-4), patient safety (items 6-12), team relationship (items 13-15) and emotion (items 16-21), The answers ranged from 1 for "strongly disagree" to 5 for "strongly agree," using Likert's 5-level scale. The final result was 21-105, with higher scores indicating higher sickness presenteeism by nurses. 2.4 Data collection 2.4.1 Pre-survey In October 2023, thirty clinical nurses from the First Hospital Affiliated to Jinzhou Medical University in Liaoning Province were chosen as the pre-survey responders using a convenience sample method[23]. All participants gave their informed consent after being informed about the goal and significance of the study by the investigator. 30 pre-survey respondents indicated that the scale had clear themes, complete structure, logical coherence, and no difficulty in semantic comprehension. Therefore, no modification was made, and the Chinese version of the SPS-N scale was finally formed. 2.4.2 Formal investigation Before the investigation, informed consent was obtained from the nursing department of the hospital. At the same time, contact the head nurses of all subjects to communicate the purpose of the study and the instructions for filling out the questionnaire. The survey's instructions made it clear that it was intended solely for use in scientific study at the outset. In addition, participants ensured that data collection was anonymous and voluntary. Distribution of questionnaires by trained members. Data collection through a combination of offline and online methods, excluding questionnaires with a response time of less than 3 min and those with a clear pattern of responses. Eventually, 503 valid surveys were received, that produces a 91.4% effective return rate. After 2 weeks, 40 nurses randomly selected from the initial participants were retested using the same questionnaire and retest reliability was analyzed. 2.5 Data analysis In this study, statistical data analysis tool used was AMOS 28.0 and SPSS 26.0. The counting data are defined by frequency and percentage, while the measurement data are described by mean and standard deviation. 2.5.1 Item analysis The critical ratio method and correlation coefficient method were used to screen the items on the scale. (1) Critical ratio method: An independent sample t-test was used to determine whether the difference between the high group (the first 27%) and the low group (the last 27%) was statistically significant. The 503 questionnaires were sorted from high to low based on the total score. Items that were found to be statistically significant will be kept. (2) Method of correlation coefficient: The correlation coefficient between 21 items and the total amount table was determined using the Pearson correlation coefficient method. Items that had a very poor association (r < 0.3) with the scale's overall score were eliminated. 2.5.2 Validity analysis (1) Content validity: Six nursing experts were asked to assess the Chinese version of SPS-N content validity using the Delphi approach., which was calculated using a Likert 4-point scale. Each item was given a score of "not relevant = 1, weakly relevant = 2, more relevant = 3, strongly relevant = 4" based on its relevance to the topic. I-CVI is the ratio of the number of experts who rated each entry 3 or 4 to the total number of experts. S-CVI is the average of I-CVI of all items[24]. (2) Construct validity: Examining the translated scale's latent factor structure with exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), The valid data of 503 cases were randomly divided into two parts, one part (n=161) was used for EFA and the other part (n=342) was used for CFA. For EFA, orthogonal rotation variance maximization and principal component analysis were chosen. AMOS was used for CFA to analyze whether the fitting index of the model was appropriate. (3) Convergent and discriminant validity: Based on the outcomes of CFA, correlation coefficients between observed variables, Average Variance Extracted (AVE), and Combined Reliability (CR) were measured. 2.5.3 Reliability analysis Retest reliability and internal consistency were applied in this study's reliability testing. To assess the internal consistency of the scale, Cronbach's α were measured for each dimension and the Chinese version of the scale. The translated scale was used for the retest reliability, and 40 nurses were chosen based on the inclusion and exclusion criteria. There was a 2-week interval between the two assessments. In order to evaluate the stability and consistency of the scale over time, the retest reliability of the two measurement scores was assessed using the Intraclass Correlation Coefficient (ICC). The scale items were then divided into two sections, and the correlation between the outcomes of each half was calculated to determine the split-half reliability. 2.5.4 Ethical consideration The Jinzhou Medical University Ethics Committee (JZMULL2023133) agreed to the study, and the research procedure complied with the committee's ethical regulations. Every person gave their informed consent prior to the data collection. 3 Results 3.1 Cross-cultural adaptation Taking into account the conventions of the Chinese language in our context and in accordance with the opinion of experts, entries 1 to 15, "Because of my health problems, ......", are replaced by "Because of my health problems, ......". The purpose of this modification is to make it easier for us Chinese to express ourselves verbally. Consideration of comprehensibility and the purpose of the scale and avoidance of ambiguity. Replace entry 16, "I am angry with my leader because I have to work even though I have health problems" with "I am unhappy with my leader because I have to work even though I have health problems". 3.2 Respondents A total of 503 study subjects met the inclusion criteria. The basic information of the subjects, such as age, sex, department, marriage and childbearing situation, forms of employment, working time, technical title, education level , income situation are displayed in Table 1 for more details on the sample’s demographic features. Table 1 Distribution of demographic characteristics Variables （Mean±SD） N % Age - 33.24±6.67 - - Sex males 33 6.6 Department Marriage and childbearing situation Forms of employment working time Occupational level educational level Income situation females medical department Surgical department maternity ward ICU operating rooms emergency department OPD paediatrics department Unmarried and childless Married and childless Married and pregnant Other formal contractual Labor dispatch 6-12 months 1-5 years 5-10 years More than 10 years nurse Nurse Practitioner Nurse-in-charge co-chief nurse and above technical secondary school college degree Bachelor's degree Master's degree 2000-3000 yuan 3001-5000 yuan 5001-7000 yuan 7001-10000 yuan More than 10,000 yuan 470 207 160 15 45 47 18 6 5 150 71 278 4 87 407 9 32 110 150 211 67 307 117 12 1 57 399 46 54 198 187 62 2 94.4 41.2 31.8 3.0 8.9 9.3 3.6 1.2 1.0 29.8 14.1 55.3 0.8 17.3 80.9 1.8 6.4 21.9 29.8 41.9 13.3 61.0 23.3 2.4 0.2 11.3 79.3 9.1 10.7 39.4 37.2 12.3 0.4 3.3 Item analysis In this study, independent sample t-test was used to analyze and identify the discrimination between high and low groups in the questionnaire. The critical ratios of 21 items were 9.015~22.837 and P<0.01. Pearson correlation method was used to analyze the correlation between the scores of each item and the total score, and the results were r=0.440~0.733 and P<0.01. Table 2 Table 2 Item analysis of Chinese version of the SPS-N Item Critical ratio Correlation item-total score P Cronbach'sα after deleting the item Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 11.711 22.837 17.916 19.457 19.361 9.015 10.365 13.716 15.150 15.316 14.455 14.104 15.408 11.232 12.184 12.002 15.932 17.156 15.356 17.399 16.128 0.440 0.582 0.587 0.659 0.691 0.498 0.601 0.660 0.697 0.689 0.679 0.689 0.821 0.607 0.644 0.698 0.733 0.725 0.706 0.702 0.704 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 0.927 0.922 0.922 0.920 0.919 0.923 0.921 0.920 0.920 0.920 0.920 0.921 0.921 0.921 0.920 0.919 0.918 0.919 0.919 0.919 0.919 3.4 Validity 3.4.1 Content validity Six experts were invited to evaluate the content validity of the Chinese version of SPS-N using the Delphi method. The I-CVI and S-CVI of the Chinese version of the SPS-N were calculated using the Likert 4-point scale. The results showed I-CVI = 0.83 to 1.00 and S-CVI = 0.910. 3.4.2 Construct validity 3.4.2.1 Exploratory factor analysis The KMO sampling fitness measure and Bartlett's test of sphericity were first tested before conducting exploratory factor analysis, and KMO values >0.7 and P<0.05 were generally considered suitable for factor analysis. The KMO value in this study was 0.890 and Bartlett's sphericity test showed an approximation of 3706.134, df=210, p<0.05. Using the principal component analysis method, the factors with characteristic value 1 are extracted, and the component matrix is obtained by orthogonal rotation of maximum variance, and only the factors with load value greater than 0.5 are set(Baris et al., 2023). Figure1 After 6 iterations of rotation and convergence, a total of 4 metrics were extracted to agree with the original scale, with a cumulative explained variance of 78.354%. Table 3 Figure1 Screening diagram for the SPS-N scale's Chinese version's exploratory factor analysis. Table 3 Factor loadings for the Chinese version of the SPS-N 21 items Item Factor 1 Factor 2 Factor 3 Factor 4 Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 - - - - - 0.734 0.830 0.844 0.889 0.888 0.756 0.739 - - - 0.584 0.788 0.875 0.843 0.881 0.807 - - - - - - - - - - - - - - - - - - - - - 0.717 0.815 0.792 0.724 0.674 - - - - - - - - - - - - - - - - - - - - - - - - - - - - 0.813 0.736 0.661 - - - - - - eigenvalue 11.328 2.520 1.606 1.001 Cumulative variance contribution rate（%） 26.844 50.637 67.139 78.354 3.4.2.2 Confirmatory factor analysis Verifying that the link between question items and factors is compatible with the hypotheses is the aim of the CFA. Model fit metrics include:CMIN/DF, RMSEA, AGFI, GFI, TLI, IFI, CFI, PGFI. According to MI, the initial model is modified e6 and e7, e16 and e17, e11 and e12 in turn. Figure2 The final model fitness index CMIN/DF was 2.527, RMSEA was 0.067, AGIF was 0.875, TLI was 0.941, IFI was 0.950, CFI was 0.949, GFI was 0.900, and PGFI was 0.692. Table 4 The structural reliability (CR) was in the range of 0.854 to 0.927 and the average variance extracted (AVE) values were 0.548 to 0.688. Table 5 Figure2 The Chinese version of the SPS-N standardized four-factor structural model (n=342) Note: F1: General performance F2: Patient safety F3: Relationships within the team F4: Emotion Table 4 Chinese version of the SPS-N CFA model fit indicator model CMIN/DF RMSEA AGFI TLI IFI CFI GFI PGFI M1 M2 Standard Fitting effect 4.205 2.527 <3 good 0.097 0.067 0.9 acceptable 0.876 0.941 >0.9 good 0.893 0.950 >0.9 good 0.892 0.949 >0.9 good 0.823 0.900 >0.9 good 0.652 0.692 >0.5 good ( Note: M1: measured value before correction; M2: corrected measured value) Table 5 Discriminant and Convergent validity of the Chinese version of the SPS-N Discriminant Validity Convergent validity Factors F1 F2 F3 F4 Item Std. Estimate SE P CR AVE F1 F2 F3 F4 0.740 0.421** 0.807 0.361** 0.598** 0.830 0.326** 0.324** 0.388** 0.815 Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 0.444 0.805 0.828 0.769 0.787 0.571 0.750 0.855 0.957 0.915 0.741 0.796 0.826 0.837 0.826 0.659 0.721 0.832 0.877 0.925 0.845 0.216 0.198 0.198 0.188 0.092 0.139 0.154 0.155 0.158 0.152 0.053 0.056 0.074 0.117 0.126 0.125 0.117 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 P<0.01 0.854 0.927 0.869 0.921 0.548 0.651 0.688 0.664 **p < 0.01 3.5 Reliability The Cronbach's α for the Chinese version of the SPS-N overall was 0.924, and the Cronbach's α for the four factors were 0.854, 0.939, 0.870, and 0.928, respectively. The Cronbach's α was 0.918 to 0.927 after deleting the question items. In addition, after 2 weeks, the re-test reliability was found to be 0.895[25].The split-half reliability was 0.750. Table 6 Table 6 Split-half reliability and re-test reliability of the Chinese version of SPS-N Factors Cronbach'sα split-half reliability re-test reliability General performance（Q1-Q5） Patient safety（Q6-Q12） 0.854 0.939 0.750 0.895 Relationships within the team（Q13-Q15） Emotions（Q16-Q21） 0.870 0.928 4 Discussion This study describes the development of the SPS-N, as well as psychometric properties. The findings support the idea that the Chinese version of the SPS-N is a multidimensional measure that covers four important areas: general performance, patient safety, team relationships, and emotions. Overall, according to the AMOS model, the Chinese version of the SPS-N scale showed a satisfactory fit. Project analysis's primary goal is to evaluate a scale's or individual item's discrimination, (that is to study whether the data can effectively distinguish between high and low levels). To avoid bias caused by a single test method, the study used the critical ratio method and the correlation coefficient method to analyze the scale items and decide on the trade-offs of the entries. This study showed that independent samples t-tests were performed for high and low subgroups, respectively, and t = 9.015 to 22.837 all > 3.0 and P < 0.01, [ 26 ]indicating strong entry discrimination. The correlation coefficients between each question item and the overall score, as determined by the Pearson correlation coefficient method, were r = 0.440 ~ 0.733, all > 0.4, and P < 0.01, suggesting a significant link between each item and the scale. The total Cronbach's α of the scale was 0.924, and although the total Cronbach's α of the scale was 0.927 after deletion of the first item, according to the discussion of Hanyi Wang[ 27 ], the items that did not have an increase in Cronbach's α of more than 0.5 after deletion of the question items were retained, so all of the 21 items should be retained. These results imply that all 21 SPS-N entries in the Chinese version are well preserved and exhibit a high degree of distinctiveness. Content validity refers to whether the entries reflect the content of the scale being measured, and the content of the scale is comprehensively evaluated by experts in the field. Six experts were asked to complete content validity tests and cultural debug the scale as part of this study. The results revealed that the scale's S-CVI = 0.910 and I-CVI = 0.83 to 1.00 were higher than the reference values[ 28 ]. This suggests that the content evaluated by the scale is well regarded by professionals and that the language of the scale is consistent with expressions in the Chinese context and easy to understand. Structural validity is the most theoretical form of validity that reflects the facts of the concept to be studied. Four metric factors were finally extracted by principal component analysis and maximum variance rotation, which were general performance, patient safety, team relationship, and emotion. It was consistent with the English version of the scale. The rotated factor loadings were all > 0.5 and there were no double-loading phenomena, meeting psychometric requirements. By validated factor analysis, CMIN/DF 0.9, and RMSEA was < 0.08.[ 29 ]The adjusted goodness-of-fit index (AGFI = 0.857) did not meet the ideal fit criterion but was close to 0.9, which was still acceptable. Possibly due to the limitations of the sample size, the rest of the indicators met the ideal value rubric, and the model fit was satisfactory, suggesting good structural validity of the scale. Convergent Validation is used to assess whether items measuring the same underlying constructs are grouped together, and the Chinese version of the SPS-N has CR values greater than 0.6 and AVE values greater than 0.5 for all four factors, indicating that the modified model has good intrinsic quality[ 30 ]. Therefore, the scale can be considered to have good convergent validity. When there is good discriminant validity between subscales, as indicated by the square root of the AVE being greater than the correlation coefficient for each individual subscale, the test of discriminant validity determines whether or not items with different constructs are classified together[ 26 ]. Internal consistency reliability refers to the homogeneity between all the questions that make up the test. Cronbach's α is less than 0.6, which is considered to be insufficient internal consistency; when it is between 0.7 and 0.8, there is a certain degree of reliability; and when it is between 0.8 and 0.9, it indicates a good degree of reliability[ 31 ].The Cronbach's α of the total scale in this study was 0.943, and the Cronbach's α of the dimensions were 0.843 to 0.944, indicating good homogeneity among the 21 items in the translated scale. Re-test reliability is used to reflect the stability and consistency of the test results of the same scale at different time points, and re-test reliability is expressed by the correlation coefficient r. r has a range of 0 to 1, and the closer it is to 1, the more reliable the retest is[ 32 ].The re-test reliability of this study was 0.896, and the re-test reliability of the dimensions ranged from 0.854 to 0.939, indicating good stability and consistency of the translated scales. Split-half reliability, the questionnaire entries are divided into two halves, which can be considered as two measurements in the shortest period of time, and the correlation coefficient between the two halves of the entries is calculated and used as the folded half reliability of the scale. When the Spearman correlation coefficient is ≧ 0.7, it represents a good split-half reliability of the scale. The split-half reliability of this study was 0.750, indicating that the split-half reliability of the instrument was acceptable. To summaries, the Chinese SPS-N scale provides strong structural validity, content validity, and reliability, making it a trustworthy instrument for assessing the effects of presenteeism on nurse productivity and performance. 5 Limitations Despite the methodological rigor of this study, there are some limitations. First, the survey was limited to a tertiary general hospital in Liaoning Province, China, using convenience sampling, which can limit the generalizability of the findings, so future studies could include more participants and validate the scale in different regions of China. Second, this study did not examine the association between the Chinese version of the SPS-N and other scales with similar conceptualizations, further validation of the relationship between other indicators related to nurse presenteeism is needed in the Chinese cultural context. 6 Conclusion The results of this study indicate that the Chinese version of the SPS-N scale has good psychometric properties in the Chinese cultural context. Nursing administrators can use the Chinese version of the SPS-N to assess the impact of presenteeism behaviors of nurses on the performance and productivity of nurses in their hospitals. At the same time, presenteeism is a public health issue of high importance in the fields of nursing management, mental health, and occupational health[ 5 ]. Nursing administrators should provide effective interventions to prevent clinical nurses from working while sick. Abbreviations SPS-N Sickness Presenteeism Scale- Nurses CMIN/DF chi-square/degree of freedom RMSEA Root-mean-square error of approximation CFI Comparative fit index TLI Tucker lewis index IFI Incremental fit index GFI Goodness-of-fit index AGFI Adjusted goodness-of-fit index PGFI Parsimony goodness-of-fit index S-CVI Scale-level content validity index I-CVI Item-level content validity index KMO The Kaiser–Meyer–Olkin EFA Exploratory factor analysis CFA Confirmatory factor analysis MI The modification indices CR Critical ration AVE Average variance extracted Declarations Acknowledgement We express our great gratitude to the participants in the study. Author contributions CL: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing-original draft, Writing-review & editing. LZ:Funding acquisition,Methodology,Project administration,Resources,Supervision, Visualization, Writing-review & editing. ZM: Investigation, Methodology, Resources.YL: Investigation, Methodology, Software. Funding The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article. Availability of data and materials The experimental data of this study are available from the authors upon request. Data will be provided by the authors upon reasonable request. Ethics statement The studies involving humans were approved by Jinzhou Medical University’s Research Ethics Review Board. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Consent for publication Not applicable. Competing interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. References Smith CM, Horne CE, Wei H: Nursing practice in modern healthcare environments: A systematic review of attributes, characteristics, and demonstrations . J Adv Nurs 2024. Li Y, Guo B, Wang Y, Lv X, Li R, Guan X, Li L, Li J, Cao Y: Serial-Multiple Mediation of Job Burnout and Fatigue in the Relationship Between Sickness Presenteeism and Productivity Loss in Nurses: A Multicenter Cross-Sectional Study . Front Public Health 2021, 9 :812737. Allemann A, Siebenhüner K, Hämmig O: Predictors of Presenteeism Among Hospital Employees-A Cross-Sectional Questionnaire-Based Study in Switzerland . J Occup Environ Med 2019, 61 (12):1004-1010. Min A, Kang M, Park H: Global prevalence of presenteeism in the nursing workforce: A meta-analysis of 28 studies from 14 countries . J Nurs Manag 2022, 30 (7):2811-2824. Homrich PHP, Dantas-Filho FF, Martins LL, Marcon ER: Presenteeism among health care workers: literature review . Rev Bras Med Trab 2020, 18 (1):97-102. Rainbow JG, Drake DA, Steege LM: Nurse Health, Work Environment, Presenteeism and Patient Safety . West J Nurs Res 2020, 42 (5):332-339. Rainbow JG, Steege LM: Presenteeism in nursing: An evolutionary concept analysis . Nurs Outlook 2017, 65 (5):615-623. Aysun K, Bayram Ş: Determining the level and cost of sickness presenteeism among hospital staff in Turkey . Int J Occup Saf Ergon 2017, 23 (4):501-509. Umann J, Guido Lde A, Grazziano Eda S: Presenteeism in hospital nurses . Rev Lat Am Enfermagem 2012, 20 (1):159-166. Shan G, Wang S, Wang W, Guo S, Li Y: Presenteeism in Nurses: Prevalence, Consequences, and Causes From the Perspectives of Nurses and Chief Nurses . Front Psychiatry 2020, 11 :584040. Letvak SA, Ruhm CJ, Gupta SN: Nurses' presenteeism and its effects on self-reported quality of care and costs . Am J Nurs 2012, 112 (2):30-38; quiz 48, 39. Cicolini G, Della Pelle C, Cerratti F, Franza M, Flacco ME: Validation of the Italian version of the Stanford Presenteeism Scale in nurses . J Nurs Manag 2016, 24 (5):598-604. Endicott J, Nee J: Endicott Work Productivity Scale (EWPS): a new measure to assess treatment effects . Psychopharmacol Bull 1997, 33 (1):13-16. Ospina MB, Dennett L, Waye A, Jacobs P, Thompson AH: A systematic review of measurement properties of instruments assessing presenteeism . Am J Manag Care 2015, 21 (2):e171-185. Lu L, L. Cooper C, Yen Lin H: A cross-cultural examination of presenteeism and supervisory support . Career Development International 2013, 18 (5):440-456. Li Y, Zhang J, Wang S, Guo S: The Effect of Presenteeism on Productivity Loss in Nurses: The Mediation of Health and the Moderation of General Self-Efficacy . Front Psychol 2019, 10 :1745. Gärtner FR, Nieuwenhuijsen K, van Dijk FJ, Sluiter JK: Psychometric properties of the Nurses Work Functioning Questionnaire (NWFQ) . PLoS One 2011, 6 (11):e26565. Shan G, Wang S, Feng K, Wang W, Guo S, Li Y: Development and Validity of the Nurse Presenteeism Questionnaire . Front Psychol 2021, 12 :679801. Baris VK, Intepeler SS, Unal A: Development and psychometric validation of the Sickness Presenteeism Scale-Nurse . Int J Nurs Pract 2023, 29 (5):e13168. Brborović H, Daka Q, Dakaj K, Brborović O: Antecedents and associations of sickness presenteeism and sickness absenteeism in nurses: A systematic review . Int J Nurs Pract 2017, 23 (6). Sharif Nia H, Kaur H, Fomani FK, Rahmatpour P, Kaveh O, Pahlevan Sharif S, Venugopal AV, Hosseini L: Psychometric Properties of the Impact of Events Scale-Revised (IES-R) Among General Iranian Population During the COVID-19 Pandemic . Front Psychiatry 2021, 12 :692498. Yu Y, Wan C, Huebner ES, Zhao X, Zeng W, Shang L: Psychometric properties of the symptom check list 90 (SCL-90) for Chinese undergraduate students . J Ment Health 2019, 28 (2):213-219. Gunawan J, Marzilli C, Aungsuroch Y: Establishing appropriate sample size for developing and validating a questionnaire in nursing research . Belitung Nurs J 2021, 7 (5):356-360. Ge Y, Zheng C, Wang X, Liu T: Psychometric properties of the Chinese version of the health behavior motivation scale: a translation and validation study . Front Psychol 2024, 15 :1279816. Li JY, Wu XX, Fan YR, Shi YX: Valuation of the cultural adaptation and psychometric properties of the Chinese version of the hidden curriculum evaluation scale in nursing education . Nurse Educ Pract 2024, 75 :103880. Liu Y, Zhang L, Li S, Li H, Huang Y: Psychometric properties of the Chinese version of the oncology nurses health behaviors determinants scale: a cross-sectional study . Front Public Health 2024, 12 :1349514. Wang HY, Wang ZQ, Chen CC, Wei WH: Cross-Cultural Adaptation and Psychometric Evaluation of the Chinese Version of the Authentic Nurse Leadership Questionnaire . Journal of Nursing Management 2024, 2024 . Ferreira LK, Filgueiras Meireles JF, de Oliveira Gomes GA, Caputo Ferreira ME: Development and Psychometric Evaluation of a Lifestyle Evaluation Instrument for Older Adults . Percept Mot Skills 2023, 130 (5):1901-1923. Asadizaker M, Ebadi A, Molavynejad S, Yadollahi S, Saki Malehi A: Development and Psychometric Evaluation of the Clinical Nursing Cultural Competence Scale . J Nurs Meas 2023, 31 (4):615-625. Azama K: A Psychometric Evaluation of the Nurse Practitioner Self-efficacy Scale . J Nurs Adm 2023, 53 (11):594-600. Shao Y, Zhang H, Zhang X, Liang Q, Zhang H, Zhang F: Chinese version of exercise dependence scale-revised: psychometric analysis and exploration of risk factors . Front Psychol 2023, 14 :1309205. Tong LK, Zhu MX, Wang SC, Cheong PL, Van IK: A Chinese Version of the Caring Dimensions Inventory: Reliability and Validity Assessment . Int J Environ Res Public Health 2021, 18 (13). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 07 May, 2025 Read the published version in BMC Nursing → Version 1 posted Editorial decision: Revision requested 26 Dec, 2024 Reviews received at journal 28 Nov, 2024 Reviews received at journal 19 Nov, 2024 Reviewers agreed at journal 18 Nov, 2024 Reviews received at journal 15 Nov, 2024 Reviewers agreed at journal 15 Nov, 2024 Reviews received at journal 08 Oct, 2024 Reviewers agreed at journal 09 Aug, 2024 Reviewers agreed at journal 22 Jul, 2024 Reviewers invited by journal 13 Jul, 2024 Editor assigned by journal 11 Jul, 2024 Submission checks completed at journal 11 Jul, 2024 First submitted to journal 05 Jul, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-4694732","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":335562901,"identity":"d957a251-ec8f-451f-bf48-133aebf6d809","order_by":0,"name":"Chuang Li","email":"","orcid":"","institution":"Jinzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Chuang","middleName":"","lastName":"Li","suffix":""},{"id":335562902,"identity":"84891a6d-26fa-4e67-9e5d-247603e598c2","order_by":1,"name":"Zhixing Meng","email":"","orcid":"","institution":"Jinzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Zhixing","middleName":"","lastName":"Meng","suffix":""},{"id":335562903,"identity":"2967f60b-db5b-43b7-ac50-0e9df687d6c8","order_by":2,"name":"Youbei Lin","email":"","orcid":"","institution":"Jinzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Youbei","middleName":"","lastName":"Lin","suffix":""},{"id":335562904,"identity":"b07f8083-6a7b-4718-aa2a-9e4a9335eb6c","order_by":3,"name":"Lan Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYDACCRBRIcFj38x88EFChQ2xWs7YyBmwsyUbPDiTRqQWxrY0YwN+HjPJh22HCOuQn9387OGXM4cTtzPzmFUksB1g4G/vTsCrhXHOMXNjmYrDiTub2cpuJPDcYZA4c3YDXi3MEglm0hJAWxoOM2+7kSDxjMFAIhe/FjaJ9G/Skm0gLQxmBQkGhwlr4ZHIMZP8CPL+YRYzhoQEIrRISOSUSYMCWbKZLVki4UAaD0G/yM9I3yb5AxiV/PyHD378+c9Gjr+9F78WEGDmQXYpQeUgwPiDKGWjYBSMglEwYgEAiURKI87+lPQAAAAASUVORK5CYII=","orcid":"","institution":"First Affiliated Hospital of Jinzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Lan","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-07-06 03:08:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4694732/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4694732/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12912-025-03113-w","type":"published","date":"2025-05-07T15:57:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":61778158,"identity":"0188678b-6ecc-4257-b406-3cbe8b48ea9c","added_by":"auto","created_at":"2024-08-05 13:05:29","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":11297,"visible":true,"origin":"","legend":"\u003cp\u003eScreening diagram for the SPS-N scale's Chinese version's exploratory factor analysis.\u003c/p\u003e","description":"","filename":"FIGURE1.png","url":"https://assets-eu.researchsquare.com/files/rs-4694732/v1/2abd602231109f890c492c2c.png"},{"id":61778157,"identity":"1e901a30-20a0-433a-acf8-d486975333c5","added_by":"auto","created_at":"2024-08-05 13:05:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":204325,"visible":true,"origin":"","legend":"\u003cp\u003eThe Chinese version of the SPS-N standardized four-factor structural model (n=342)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote: \u003c/em\u003eF1: General performance F2: Patient safety F3: Relationships within the team F4: Emotion\u003c/p\u003e","description":"","filename":"FIGURE2.png","url":"https://assets-eu.researchsquare.com/files/rs-4694732/v1/53dc0c754ab3183f6bce37af.png"},{"id":82538158,"identity":"3b6d025e-fafb-4f9d-bdbd-1fdc20e0fed9","added_by":"auto","created_at":"2025-05-12 16:10:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2478523,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4694732/v1/a9167bd0-07b4-4ca5-b741-0d42849f6c53.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cross-cultural adaptation and psychometric evaluation of the Chinese version of the Sickness Presenteeism Scale- Nurses:A cross-sectional study","fulltext":[{"header":"1 Background","content":"\u003cp\u003eWith the gradual improvement of the medical security system, the demand for high-quality services by patients is also increasing, and nurses have become important caregivers for patients and the main implementers of nursing operations[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].Nonetheless, presenteeism is quite widespread among nurses and is three to four times greater than in other industries because of shift work, a severe workload, job insecurity, a poor working environment, and other factors[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Presenteeism is the term used to describe the situation in which workers report for duty when ill and believe they should request sick time[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Nurses' presenteeism not only negatively impacts patients' physical and mental well-being but also lowers their standard of nursing care and interferes with patient treatment and rehabilitation[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In addition, there is a negative impact on nurses' job performance, motivation, satisfaction, and commitment to work[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Reduced competence means a loss of organizational productivity, which can ultimately result in serious financial losses[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. According to reports of head nurses and nurses, the yearly economic losses resulting from presenteeism amount to 2.88\u0026nbsp;billion yuan and 4.38\u0026nbsp;billion yuan, respectively, in Henan Province according to scholars. Moreover[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], Letvak, a team of foreign scholars, conducted a study on nurses in the United States of North Carolina, and found that the annual per capita loss due to nurses' presenteeism behavior ranged from 1,346 to 9,000 US dollars[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, it is especially important to find suitable tools to evaluate the presenteeism behavior of nurses and reduce the negative impact of presenteeism.\u003c/p\u003e \u003cp\u003eCurrently, the tools used to evaluate presenteeism are the Stanford Presenteeism Scale[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], Endicott Work Productivity Scale[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], Health and Work Questionnaire [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and the Luo Lu version of the presenteeism scale[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The above four assessment tools are applicable to the general occupational group and do not involve the transformation and measurement of productivity loss[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Furthermore, the Nurses Work Functioning Questionnaire (NWFQ) and Nurse Presenteeism Questionnaire (NPQ) can also be used to evaluate presenteeism.\u003c/p\u003e \u003cp\u003eHowever, the NWFQ is concerned with the impairment of work function caused by common mental disorders[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], the NPQ assesses whether nurses report working when they have different health issues[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].Although the NWFQ and NPQ are tools developed for evaluating nurses, neither can be used effectively to access the effect of presenteeism on nurses' productivity and work output.\u003c/p\u003e \u003cp\u003eDue to the lack of an evaluation instrument to gauge how presenteeism practices affect nurses' productivity at work and the quality of the medical treatment they provide, in 2023, the Turkish scholar Visser Karani Baris successfully developed the Sickness Presenteeism Scale-Nurse(SPS-N)[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].The SPS-N is a clinical tool based on evaluating nurses' general performance, patient safety, team relationships and emotions. Additionally, a four-factor framework that bridges the gap between single-dimensional measurement methods and the scale offers a thorough and reliable evaluation of nurses' presenteeism from a variety of levels and viewpoints[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].The SPS-N was translated into Chinese for this study, and in light of the significant prevalence of presenteeism among nurses, its validity and reliability were confirmed among Chinese clinical nurses.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn 2023, from October 1 to February, a cross-sectional study was conducted. A convenience sampling method was used to select clinical nurses from the First Hospital of Jinzhou Medical University in Liaoning Province. Criteria for inclusion:①Licensed Nurse Practitioner with at least 6 months of experience as a hospital nurse.②Voluntary participation in research on this topic. Criteria for exclusion:①Nurses who left their clinical posts due to study abroad, vacation, maternity leave and other reasons during the investigation.②No nurses working with illness in the last month.③Nurses in internships or advanced training at the surveyed hospitals.\u003c/p\u003e\n\u003cp\u003eEstimate the sample size based on Kendall\u0026apos;s estimation method at 5-10 times the number of questionnaire entries, taking into account a sample attrition rate of 10 to 20% , preliminary calculations of the sample size for this study ranged from 116 to 252 cases, Meanwhile, in order to meet the requirements of sample data of not less than 100 cases in exploratory factor analysis (EFA) and sample size of at least 200 cases in validation factor analysis (CFA)[21]. Ultimately, the plan is to recruit 550 study participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Translation and Cross-cultural adaptation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, the original author was contacted by email for authorization, and then the SPS-N scale was translated into Chinese version according to Brislin translation model[22]:\u003c/p\u003e\n\u003cp\u003eThe SPS-N was developed by the team of Professor Veysel Karani Baris based on a multidisciplinary theory, including work performance (items 1-4), patient safety (items 6-12), team relationship (items 13-15) and emotion (items 16-21), a total of 21 items, using the Likert 5-level scoring method, with responses ranging from 1 \u0026quot;strongly disagree\u0026quot; to 5 \u0026quot;strongly agree\u0026quot;. The total score is 21-105, with higher scores indicating higher sickness presenteeism among nurses. The original scale has good reliability and validity, and it tested the reliability and validity of 619 nurses living in 55 different cities in Turkey. The total Cronbach\u0026apos;s \u0026alpha; value was calculated as 0.928, the Cronbach\u0026apos;s \u0026alpha; value of the sub-dimension was calculated as 0.815~0.903, and the composite reliability value was calculated as 0.804~0.903[19].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e-Step 1-\u003c/em\u003eThe English version of the SPS-N was independently translated into the Chinese versions S1 and S2 by two students pursuing graduate nursing education and were native Chinese speakers with English proficiency up to level 6. The first author integrated the Chinese version of the scales S1 and S2, and fully discussed and modified them to form the Chinese version of the scale S.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e-Step 2-\u003c/em\u003eThe Chinese version of Scale S was independently back-translated by a Doctor of Nursing Science and a Master\u0026apos;s Degree in English (Medical English direction) who had never been in contact with the initial scale, resulting in the English versions of Scale SS1 and SS2.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e-Step 3-\u003c/em\u003eA professor in nursing management and an associate professor in clinical nursing integrate the back-translated version so that the semantic consistency rate reaches more than 95% to form the Chinese version to form the back-translated version of SS.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e-Step 4-\u003c/em\u003eAccording to the cultural adaptation guidelines, a total of six experts were invited to conduct two rounds of evaluation of the Chinese version of the SPS-N by e-mail and on-site consultation，achieving a balance between idiom conceptual equivalency and cultural adaptation in order to align language expressions with continental linguistic norms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Measurement and instruments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter reviewing the literature, the researcher designed a questionnaire to investigate the general demographic data of nurses, including: gender, age, department, working years, marriage and childbirth, etc.\u003c/p\u003e\n\u003cp\u003eChinese version of the Sickness Presenteeism Scale-Nurse, including 21 items in four dimensions: general performance (items 1-4), patient safety (items 6-12), team relationship (items 13-15) and emotion (items 16-21), The answers ranged from 1 for \u0026quot;strongly disagree\u0026quot; to 5 for \u0026quot;strongly agree,\u0026quot; using Likert\u0026apos;s 5-level scale. The final result was 21-105, with higher scores indicating higher sickness presenteeism by nurses.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Data collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.1 Pre-survey\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In October 2023, thirty clinical nurses from the First Hospital Affiliated to Jinzhou Medical University in Liaoning Province were chosen as the pre-survey responders using a convenience sample method[23]. All participants gave their informed consent after being informed about the goal and significance of the study by the investigator. 30 pre-survey respondents indicated that the scale had clear themes, complete structure, logical coherence, and no difficulty in semantic comprehension. Therefore, no modification was made, and the Chinese version of the SPS-N scale was finally formed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4.2 Formal investigation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore the investigation, informed consent was obtained from the nursing department of the hospital. At the same time, contact the head nurses of all subjects to communicate the purpose of the study and the instructions for filling out the questionnaire. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe survey\u0026apos;s instructions made it clear that it was intended solely for use in scientific study at the outset. In addition, participants ensured that data collection was anonymous and voluntary.\u003c/p\u003e\n\u003cp\u003eDistribution of questionnaires by trained members. Data collection through a combination of offline and online methods, excluding questionnaires with a response time of less than 3 min and those with a clear pattern of responses. Eventually, 503 valid surveys were received, that produces a 91.4% effective return rate. After 2 weeks, 40 nurses randomly selected from the initial participants were retested using the same questionnaire and retest reliability was analyzed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 Data analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, statistical data analysis tool used was AMOS 28.0 and SPSS 26.0. The counting data are defined by frequency and percentage, while the measurement data are described by mean and standard deviation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5.1 Item analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe critical ratio method and correlation coefficient method were used to screen the items on the scale. (1) Critical ratio method: An independent sample t-test was used to determine whether the difference between the high group (the first 27%) and the low group (the last 27%) was statistically significant. The 503 questionnaires were sorted from high to low based on the total score. Items that were found to be statistically significant will be kept. (2) Method of correlation coefficient: The correlation coefficient between 21 items and the total amount table was determined using the Pearson correlation coefficient method. Items that had a very poor association (r \u0026lt; 0.3) with the scale\u0026apos;s overall score were eliminated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5.2 Validity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(1) Content validity: Six nursing experts were asked to assess the Chinese version of SPS-N content validity using the Delphi approach., which was calculated using a Likert 4-point scale. Each item was given a score of \u0026quot;not relevant = 1, weakly relevant = 2, more relevant = 3, strongly relevant = 4\u0026quot; based on its relevance to the topic. I-CVI is the ratio of the number of experts who rated each entry 3 or 4 to the total number of experts. S-CVI is the average of I-CVI of all items[24].\u003c/p\u003e\n\u003cp\u003e(2) Construct validity: Examining the translated scale\u0026apos;s latent factor structure with exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), The valid data of 503 cases were randomly divided into two parts, one part (n=161) was used for EFA and the other part (n=342) was used for CFA. For EFA, orthogonal rotation variance maximization and principal component analysis were chosen. AMOS was used for CFA to analyze whether the fitting index of the model was appropriate.\u003c/p\u003e\n\u003cp\u003e(3) Convergent and discriminant validity: Based on the outcomes of CFA, correlation coefficients between observed variables, Average Variance Extracted (AVE), and Combined Reliability (CR) were measured.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5.3 Reliability analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRetest reliability and internal consistency were applied in this study\u0026apos;s reliability testing. To assess the internal consistency of the scale, Cronbach\u0026apos;s\u0026nbsp;\u0026alpha;\u0026nbsp;were measured for each dimension and the Chinese version of the scale. The translated scale was used for the retest reliability, and 40 nurses were chosen based on the inclusion and exclusion criteria. There was a 2-week interval between the two assessments. In order to evaluate the stability and consistency of the scale over time, the retest reliability of the two measurement scores was assessed using the Intraclass Correlation Coefficient (ICC). The scale items were then divided into two sections, and the correlation between the outcomes of each half was calculated to determine the split-half reliability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5.4 Ethical consideration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Jinzhou Medical University Ethics Committee (JZMULL2023133) agreed to the study, and the research procedure complied with the committee\u0026apos;s ethical regulations. Every person gave their informed consent prior to the data collection.\u003c/p\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Cross-cultural adaptation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTaking into account the conventions of the Chinese language in our context and in accordance with the opinion of experts, entries 1 to 15, \u0026quot;Because of my health problems, ......\u0026quot;, are replaced by \u0026quot;Because of my health problems, ......\u0026quot;. The purpose of this modification is to make it easier for us Chinese to express ourselves verbally. Consideration of comprehensibility and the purpose of the scale and avoidance of ambiguity. Replace entry 16, \u0026quot;I am angry with my leader because I have to work even though I have health problems\u0026quot; with \u0026quot;I am unhappy with my leader because I have to work even though I have health problems\u0026quot;.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Respondents\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 503 study subjects met the inclusion criteria. The basic information of the subjects, such as age, sex, department, marriage and childbearing situation, forms of employment, working time, technical title, education level , income situation are displayed in\u003cstrong\u003e\u0026nbsp;Table 1\u003c/strong\u003e for more details on the sample\u0026rsquo;s demographic features.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Distribution of demographic characteristics\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"699\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"45.779685264663804%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.30758226037196%\" valign=\"top\"\u003e\n \u003cp\u003e（Mean\u0026plusmn;SD）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88412017167382%\" valign=\"top\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.028612303290416%\" valign=\"top\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.17310443490701%\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.606580829756794%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.30758226037196%\" valign=\"top\"\u003e\n \u003cp\u003e33.24\u0026plusmn;6.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88412017167382%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.028612303290416%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.17310443490701%\" valign=\"top\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.606580829756794%\" valign=\"top\"\u003e\n \u003cp\u003emales\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.30758226037196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88412017167382%\" valign=\"top\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.028612303290416%\" valign=\"top\"\u003e\n \u003cp\u003e6.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"21.17310443490701%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDepartment\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eMarriage and childbearing situation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eForms of employment\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eworking time\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eOccupational level\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eeducational level\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIncome situation\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.606580829756794%\" valign=\"top\"\u003e\n \u003cp\u003efemales\u003cbr\u003e\u0026nbsp;medical department\u003c/p\u003e\n \u003cp\u003eSurgical department\u003c/p\u003e\n \u003cp\u003ematernity ward\u003c/p\u003e\n \u003cp\u003eICU\u003c/p\u003e\n \u003cp\u003eoperating rooms\u003c/p\u003e\n \u003cp\u003eemergency department\u003c/p\u003e\n \u003cp\u003eOPD\u003c/p\u003e\n \u003cp\u003epaediatrics department\u003c/p\u003e\n \u003cp\u003eUnmarried and childless\u003c/p\u003e\n \u003cp\u003eMarried and childless\u003c/p\u003e\n \u003cp\u003eMarried and pregnant\u003c/p\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003cp\u003eformal\u003c/p\u003e\n \u003cp\u003econtractual\u003c/p\u003e\n \u003cp\u003eLabor dispatch\u003c/p\u003e\n \u003cp\u003e6-12 months\u003c/p\u003e\n \u003cp\u003e1-5 years\u003c/p\u003e\n \u003cp\u003e5-10 years\u003c/p\u003e\n \u003cp\u003eMore than 10 years\u003c/p\u003e\n \u003cp\u003enurse\u003c/p\u003e\n \u003cp\u003eNurse Practitioner\u003c/p\u003e\n \u003cp\u003eNurse-in-charge\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;co-chief nurse and above\u003c/p\u003e\n \u003cp\u003etechnical secondary school\u003c/p\u003e\n \u003cp\u003ecollege degree\u003c/p\u003e\n \u003cp\u003eBachelor\u0026apos;s degree\u003c/p\u003e\n \u003cp\u003eMaster\u0026apos;s degree\u003c/p\u003e\n \u003cp\u003e2000-3000 yuan\u003c/p\u003e\n \u003cp\u003e3001-5000 yuan\u003c/p\u003e\n \u003cp\u003e5001-7000 yuan\u003c/p\u003e\n \u003cp\u003e7001-10000 yuan\u003c/p\u003e\n \u003cp\u003eMore than 10,000 yuan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.30758226037196%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.88412017167382%\" valign=\"top\"\u003e\n \u003cp\u003e470\u003c/p\u003e\n \u003cp\u003e207\u003c/p\u003e\n \u003cp\u003e160\u003c/p\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003cp\u003e278\u003c/p\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003cp\u003e407\u003c/p\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003cp\u003e211\u003c/p\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003cp\u003e307\u003c/p\u003e\n \u003cp\u003e117\u003c/p\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003cp\u003e399\u003c/p\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003cp\u003e198\u003c/p\u003e\n \u003cp\u003e187\u003c/p\u003e\n \u003cp\u003e62\u003c/p\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.028612303290416%\" valign=\"top\"\u003e\n \u003cp\u003e94.4\u003c/p\u003e\n \u003cp\u003e41.2\u003c/p\u003e\n \u003cp\u003e31.8\u003c/p\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003cp\u003e8.9\u003c/p\u003e\n \u003cp\u003e9.3\u003c/p\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003cp\u003e29.8\u003c/p\u003e\n \u003cp\u003e14.1\u003c/p\u003e\n \u003cp\u003e55.3\u003c/p\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003cp\u003e17.3\u003c/p\u003e\n \u003cp\u003e80.9\u003c/p\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003cp\u003e6.4\u003c/p\u003e\n \u003cp\u003e21.9\u003c/p\u003e\n \u003cp\u003e29.8\u003c/p\u003e\n \u003cp\u003e41.9\u003c/p\u003e\n \u003cp\u003e13.3\u003c/p\u003e\n \u003cp\u003e61.0\u003c/p\u003e\n \u003cp\u003e23.3\u003c/p\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003cp\u003e11.3\u003c/p\u003e\n \u003cp\u003e79.3\u003c/p\u003e\n \u003cp\u003e9.1\u003c/p\u003e\n \u003cp\u003e10.7\u003c/p\u003e\n \u003cp\u003e39.4\u003c/p\u003e\n \u003cp\u003e37.2\u003c/p\u003e\n \u003cp\u003e12.3\u003c/p\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Item analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;In this study, independent sample t-test was used to analyze and identify the discrimination between high and low groups in the questionnaire. The critical ratios of 21 items were 9.015~22.837 and P\u0026lt;0.01. Pearson correlation method was used to analyze the correlation between the scores of each item and the total score, and the results were r=0.440~0.733 and P\u0026lt;0.01. \u003cstrong\u003eTable 2\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Item analysis of Chinese version of the SPS-N\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"601\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.314475873544094%\" valign=\"top\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.475873544093178%\" valign=\"top\"\u003e\n \u003cp\u003eCritical ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.62063227953411%\" valign=\"top\"\u003e\n \u003cp\u003eCorrelation item-total score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.314475873544094%\" valign=\"top\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.27454242928452%\" valign=\"top\"\u003e\n \u003cp\u003eCronbach\u0026apos;s\u0026alpha;\u0026nbsp;after deleting the item\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"11.314475873544094%\" valign=\"top\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003cp\u003eQ5\u003c/p\u003e\n \u003cp\u003eQ6\u003c/p\u003e\n \u003cp\u003eQ7\u003c/p\u003e\n \u003cp\u003eQ8\u003c/p\u003e\n \u003cp\u003eQ9\u003c/p\u003e\n \u003cp\u003eQ10\u003c/p\u003e\n \u003cp\u003eQ11\u003c/p\u003e\n \u003cp\u003eQ12\u003c/p\u003e\n \u003cp\u003eQ13\u003c/p\u003e\n \u003cp\u003eQ14\u003c/p\u003e\n \u003cp\u003eQ15\u003c/p\u003e\n \u003cp\u003eQ16\u003c/p\u003e\n \u003cp\u003eQ17\u003c/p\u003e\n \u003cp\u003eQ18\u003c/p\u003e\n \u003cp\u003eQ19\u003c/p\u003e\n \u003cp\u003eQ20\u003c/p\u003e\n \u003cp\u003eQ21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.475873544093178%\" valign=\"top\"\u003e\n \u003cp\u003e11.711\u003c/p\u003e\n \u003cp\u003e22.837\u003c/p\u003e\n \u003cp\u003e17.916\u003c/p\u003e\n \u003cp\u003e19.457\u003c/p\u003e\n \u003cp\u003e19.361\u003c/p\u003e\n \u003cp\u003e9.015\u003c/p\u003e\n \u003cp\u003e10.365\u003c/p\u003e\n \u003cp\u003e13.716\u003c/p\u003e\n \u003cp\u003e15.150\u003c/p\u003e\n \u003cp\u003e15.316\u003c/p\u003e\n \u003cp\u003e14.455\u003c/p\u003e\n \u003cp\u003e14.104\u003c/p\u003e\n \u003cp\u003e15.408\u003c/p\u003e\n \u003cp\u003e11.232\u003c/p\u003e\n \u003cp\u003e12.184\u003c/p\u003e\n \u003cp\u003e12.002\u003c/p\u003e\n \u003cp\u003e15.932\u003c/p\u003e\n \u003cp\u003e17.156\u003c/p\u003e\n \u003cp\u003e15.356\u003c/p\u003e\n \u003cp\u003e17.399\u003c/p\u003e\n \u003cp\u003e16.128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.62063227953411%\" valign=\"top\"\u003e\n \u003cp\u003e0.440\u003c/p\u003e\n \u003cp\u003e0.582\u003c/p\u003e\n \u003cp\u003e0.587\u003c/p\u003e\n \u003cp\u003e0.659\u003c/p\u003e\n \u003cp\u003e0.691\u003c/p\u003e\n \u003cp\u003e0.498\u003c/p\u003e\n \u003cp\u003e0.601\u003c/p\u003e\n \u003cp\u003e0.660\u003c/p\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003cp\u003e0.689\u003c/p\u003e\n \u003cp\u003e0.679\u003c/p\u003e\n \u003cp\u003e0.689\u003c/p\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003cp\u003e0.607\u003c/p\u003e\n \u003cp\u003e0.644\u003c/p\u003e\n \u003cp\u003e0.698\u003c/p\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003cp\u003e0.725\u003c/p\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003cp\u003e0.702\u003c/p\u003e\n \u003cp\u003e0.704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.314475873544094%\" valign=\"top\"\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.27454242928452%\" valign=\"top\"\u003e\n \u003cp\u003e0.927\u003c/p\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003cp\u003e0.919\u003c/p\u003e\n \u003cp\u003e0.923\u003c/p\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003cp\u003e0.919\u003c/p\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003cp\u003e0.919\u003c/p\u003e\n \u003cp\u003e0.919\u003c/p\u003e\n \u003cp\u003e0.919\u003c/p\u003e\n \u003cp\u003e0.919\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Validity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.1 Content validity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSix experts were invited to evaluate the content validity of the Chinese version of SPS-N using the Delphi method. The I-CVI and S-CVI of the Chinese version of the SPS-N were calculated using the Likert 4-point scale. The results showed I-CVI = 0.83 to 1.00 and S-CVI = 0.910.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.2 Construct validity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.2.1 Exploratory factor analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe KMO sampling fitness measure and Bartlett\u0026apos;s test of sphericity were first tested before conducting exploratory factor analysis, and KMO values \u0026gt;0.7 and P\u0026lt;0.05 were generally considered suitable for factor analysis. The KMO value in this study was 0.890 and Bartlett\u0026apos;s sphericity test showed an approximation of 3706.134, df=210, p\u0026lt;0.05. Using the principal component analysis method, the factors with characteristic value 1 are extracted, and the component matrix is obtained by orthogonal rotation of maximum variance, and only the factors with load value greater than 0.5 are set(Baris et al., 2023).\u003cstrong\u003eFigure1\u0026nbsp;\u003c/strong\u003eAfter 6 iterations of rotation and convergence, a total of 4 metrics were extracted to agree with the original scale, with a cumulative explained variance of 78.354%.\u003cstrong\u003eTable 3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure1\u0026nbsp;\u003c/strong\u003eScreening diagram for the SPS-N scale\u0026apos;s Chinese version\u0026apos;s exploratory factor analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Factor loadings for the Chinese version of the SPS-N 21 items\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"706\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.27762039660057%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eItem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003eFactor\u0026nbsp;\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003eFactor\u0026nbsp;\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003eFactor\u0026nbsp;\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.005665722379604%\" valign=\"top\"\u003e\n \u003cp\u003eFactor\u0026nbsp;\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.27762039660057%\" valign=\"top\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003cp\u003eQ5\u003c/p\u003e\n \u003cp\u003eQ6\u003c/p\u003e\n \u003cp\u003eQ7\u003c/p\u003e\n \u003cp\u003eQ8\u003c/p\u003e\n \u003cp\u003eQ9\u003c/p\u003e\n \u003cp\u003eQ10\u003c/p\u003e\n \u003cp\u003eQ11\u003c/p\u003e\n \u003cp\u003eQ12\u003c/p\u003e\n \u003cp\u003eQ13\u003c/p\u003e\n \u003cp\u003eQ14\u003c/p\u003e\n \u003cp\u003eQ15\u003c/p\u003e\n \u003cp\u003eQ16\u003c/p\u003e\n \u003cp\u003eQ17\u003c/p\u003e\n \u003cp\u003eQ18\u003c/p\u003e\n \u003cp\u003eQ19\u003c/p\u003e\n \u003cp\u003eQ20\u003c/p\u003e\n \u003cp\u003eQ21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003cp\u003e0.844\u003c/p\u003e\n \u003cp\u003e0.889\u003c/p\u003e\n \u003cp\u003e0.888\u003c/p\u003e\n \u003cp\u003e0.756\u003c/p\u003e\n \u003cp\u003e0.739\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.584\u003c/p\u003e\n \u003cp\u003e0.788\u003c/p\u003e\n \u003cp\u003e0.875\u003c/p\u003e\n \u003cp\u003e0.843\u003c/p\u003e\n \u003cp\u003e0.881\u003c/p\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003e0.717\u003c/p\u003e\n \u003cp\u003e0.815\u003c/p\u003e\n \u003cp\u003e0.792\u003c/p\u003e\n \u003cp\u003e0.724\u003c/p\u003e\n \u003cp\u003e0.674\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.005665722379604%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e0.813\u003c/p\u003e\n \u003cp\u003e0.736\u003c/p\u003e\n \u003cp\u003e0.661\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.27762039660057%\" valign=\"top\"\u003e\n \u003cp\u003eeigenvalue\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003e11.328\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003e2.520\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003e1.606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.005665722379604%\" valign=\"top\"\u003e\n \u003cp\u003e1.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"34.27762039660057%\" valign=\"top\"\u003e\n \u003cp\u003eCumulative variance contribution rate（%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003e26.844\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003e50.637\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.572237960339944%\" valign=\"top\"\u003e\n \u003cp\u003e67.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.005665722379604%\" valign=\"top\"\u003e\n \u003cp\u003e78.354\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e3.4.2.2 Confirmatory factor analysis\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVerifying that the link between question items and factors is compatible with the hypotheses is the aim of the CFA. Model fit metrics include:CMIN/DF, RMSEA, AGFI, GFI, TLI, IFI, CFI, PGFI. According to MI, the initial model is modified e6 and e7, e16 and e17, e11 and e12 in turn. \u003cstrong\u003eFigure2\u0026nbsp;\u003c/strong\u003eThe final model fitness index CMIN/DF was 2.527, RMSEA was 0.067, AGIF was 0.875, TLI was 0.941, IFI was 0.950, CFI was 0.949, GFI was 0.900, and PGFI was 0.692.\u003cstrong\u003eTable 4\u003c/strong\u003e The structural reliability (CR) was in the range of 0.854 to 0.927 and the average variance extracted (AVE) values were 0.548 to 0.688. \u003cstrong\u003eTable 5\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure2\u0026nbsp;\u003c/strong\u003eThe Chinese version of the SPS-N standardized four-factor structural model (n=342)\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote:\u0026nbsp;\u003c/em\u003eF1: General performance \u0026nbsp; F2: Patient safety \u0026nbsp; F3: Relationships within the team \u0026nbsp;F4: Emotion\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e Chinese version of the SPS-N CFA model fit indicator\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"616\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.612377850162865%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003emodel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCMIN/DF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRMSEA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAGFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTLI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eIFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eGFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ePGFI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"16.612377850162865%\" valign=\"top\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003cp\u003eM2\u003c/p\u003e\n \u003cp\u003eStandard\u003c/p\u003e\n \u003cp\u003eFitting effect\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e4.205\u003c/p\u003e\n \u003cp\u003e2.527\u003c/p\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.08\u003c/p\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003cp\u003e\u0026gt;0.9\u003c/p\u003e\n \u003cp\u003eacceptable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e0.876\u003c/p\u003e\n \u003cp\u003e0.941\u003c/p\u003e\n \u003cp\u003e\u0026gt;0.9\u003c/p\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003cp\u003e0.950\u003c/p\u003e\n \u003cp\u003e\u0026gt;0.9\u003c/p\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e0.892\u003c/p\u003e\n \u003cp\u003e0.949\u003c/p\u003e\n \u003cp\u003e\u0026gt;0.9\u003c/p\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003cp\u003e0.900\u003c/p\u003e\n \u003cp\u003e\u0026gt;0.9\u003c/p\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.423452768729641%\" valign=\"top\"\u003e\n \u003cp\u003e0.652\u003c/p\u003e\n \u003cp\u003e0.692\u003c/p\u003e\n \u003cp\u003e\u0026gt;0.5\u003c/p\u003e\n \u003cp\u003egood\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e(\u003cem\u003eNote:\u003c/em\u003e M1: measured value before correction; M2: corrected measured value)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e Discriminant and Convergent validity of the Chinese version of the SPS-N\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"654\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"40.0611620795107%\" colspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiscriminant Validity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"59.9388379204893%\" colspan=\"6\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eConvergent validity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.837173579109063%\" valign=\"top\"\u003e\n \u003cp\u003eFactors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.294930875576037%\" valign=\"top\"\u003e\n \u003cp\u003eF1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.755760368663594%\" valign=\"top\"\u003e\n \u003cp\u003eF2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\" valign=\"top\"\u003e\n \u003cp\u003eF3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\" valign=\"top\"\u003e\n \u003cp\u003eF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74347158218126%\" valign=\"top\"\u003e\n \u003cp\u003eItem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.36405529953917%\" valign=\"top\"\u003e\n \u003cp\u003eStd. Estimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7588325652841785%\" valign=\"top\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.680491551459293%\" valign=\"top\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7588325652841785%\" valign=\"top\"\u003e\n \u003cp\u003eCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\" valign=\"top\"\u003e\n \u003cp\u003eAVE\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"5.837173579109063%\" valign=\"top\"\u003e\n \u003cp\u003eF1\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eF2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eF3\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eF4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.294930875576037%\" valign=\"top\"\u003e\n \u003cp\u003e0.740\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.755760368663594%\" valign=\"top\"\u003e\n \u003cp\u003e0.421**\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.807\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\" valign=\"top\"\u003e\n \u003cp\u003e0.361**\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.598**\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.830\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\" valign=\"top\"\u003e\n \u003cp\u003e0.326**\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.324**\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.388**\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.815\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.74347158218126%\" valign=\"top\"\u003e\n \u003cp\u003eQ1\u003c/p\u003e\n \u003cp\u003eQ2\u003c/p\u003e\n \u003cp\u003eQ3\u003c/p\u003e\n \u003cp\u003eQ4\u003c/p\u003e\n \u003cp\u003eQ5\u003c/p\u003e\n \u003cp\u003eQ6\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ7\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ8\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ9\u003c/p\u003e\n \u003cp\u003eQ10\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ11\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ12\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ13\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ14\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ15\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ16\u003c/p\u003e\n \u003cp\u003eQ17\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ18\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ19\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ20\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eQ21\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.36405529953917%\" valign=\"top\"\u003e\n \u003cp\u003e0.444\u003c/p\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003cp\u003e0.828\u003c/p\u003e\n \u003cp\u003e0.769\u003c/p\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003cp\u003e0.855\u003c/p\u003e\n \u003cp\u003e0.957\u003c/p\u003e\n \u003cp\u003e0.915\u003c/p\u003e\n \u003cp\u003e0.741\u003c/p\u003e\n \u003cp\u003e0.796\u003c/p\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003cp\u003e0.837\u003c/p\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003cp\u003e0.659\u003c/p\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003cp\u003e0.832\u003c/p\u003e\n \u003cp\u003e0.877\u003c/p\u003e\n \u003cp\u003e0.925\u003c/p\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7588325652841785%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.216\u003c/p\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003cp\u003e0.188\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003cp\u003e0.139\u003c/p\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.680491551459293%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01 P\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01 P\u0026lt;0.01 P\u0026lt;0.01 P\u0026lt;0.01 P\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01 P\u0026lt;0.01\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eP\u0026lt;0.01 P\u0026lt;0.01 P\u0026lt;0.01 P\u0026lt;0.01 P\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.7588325652841785%\" valign=\"top\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.927\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.869\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.921\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.602150537634408%\" valign=\"top\"\u003e\n \u003cp\u003e0.548\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.651\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.688\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cem\u003e**p \u0026lt; 0.01\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Reliability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Cronbach\u0026apos;s\u0026nbsp;\u0026alpha;\u0026nbsp;for the Chinese version of the SPS-N overall was 0.924, and the Cronbach\u0026apos;s\u0026nbsp;\u0026alpha;\u0026nbsp;for the four factors were 0.854, 0.939, 0.870, and 0.928, respectively. The Cronbach\u0026apos;s\u0026nbsp;\u0026alpha;\u0026nbsp;was 0.918 to 0.927 after deleting the question items. In addition, after 2 weeks, the re-test reliability was found to be 0.895[25].The split-half reliability was 0.750. \u003cstrong\u003eTable 6\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6\u003c/strong\u003e Split-half reliability\u0026nbsp;and re-test reliability of the Chinese version of SPS-N\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.149068322981364%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFactors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.596273291925465%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCronbach\u0026apos;s\u0026alpha;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.273291925465838%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003esplit-half reliability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.981366459627328%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ere-test reliability\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"41.149068322981364%\" valign=\"top\"\u003e\n \u003cp\u003eGeneral performance（Q1-Q5）\u003c/p\u003e\n \u003cp\u003ePatient safety（Q6-Q12）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.596273291925465%\" valign=\"top\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003cp\u003e0.939\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.273291925465838%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.981366459627328%\" valign=\"top\"\u003e\n \u003cp\u003e0.895\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.26824457593688%\" valign=\"top\"\u003e\n \u003cp\u003eRelationships within the team（Q13-Q15）\u003c/p\u003e\n \u003cp\u003eEmotions（Q16-Q21）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.54043392504931%\" valign=\"top\"\u003e\n \u003cp\u003e0.870\u003c/p\u003e\n \u003cp\u003e0.928\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.191321499013807%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis study describes the development of the SPS-N, as well as psychometric properties. The findings support the idea that the Chinese version of the SPS-N is a multidimensional measure that covers four important areas: general performance, patient safety, team relationships, and emotions. Overall, according to the AMOS model, the Chinese version of the SPS-N scale showed a satisfactory fit.\u003c/p\u003e \u003cp\u003eProject analysis's primary goal is to evaluate a scale's or individual item's discrimination, (that is to study whether the data can effectively distinguish between high and low levels). To avoid bias caused by a single test method, the study used the critical ratio method and the correlation coefficient method to analyze the scale items and decide on the trade-offs of the entries. This study showed that independent samples t-tests were performed for high and low subgroups, respectively, and t\u0026thinsp;=\u0026thinsp;9.015 to 22.837 all \u0026gt;\u0026thinsp;3.0 and P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]indicating strong entry discrimination. The correlation coefficients between each question item and the overall score, as determined by the Pearson correlation coefficient method, were r\u0026thinsp;=\u0026thinsp;0.440\u0026thinsp;~\u0026thinsp;0.733, all \u0026gt;\u0026thinsp;0.4, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.01, suggesting a significant link between each item and the scale. The total Cronbach's α of the scale was 0.924, and although the total Cronbach's α of the scale was 0.927 after deletion of the first item, according to the discussion of Hanyi Wang[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], the items that did not have an increase in Cronbach's α of more than 0.5 after deletion of the question items were retained, so all of the 21 items should be retained. These results imply that all 21 SPS-N entries in the Chinese version are well preserved and exhibit a high degree of distinctiveness.\u003c/p\u003e \u003cp\u003eContent validity refers to whether the entries reflect the content of the scale being measured, and the content of the scale is comprehensively evaluated by experts in the field. Six experts were asked to complete content validity tests and cultural debug the scale as part of this study. The results revealed that the scale's S-CVI\u0026thinsp;=\u0026thinsp;0.910 and I-CVI\u0026thinsp;=\u0026thinsp;0.83 to 1.00 were higher than the reference values[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This suggests that the content evaluated by the scale is well regarded by professionals and that the language of the scale is consistent with expressions in the Chinese context and easy to understand.\u003c/p\u003e \u003cp\u003eStructural validity is the most theoretical form of validity that reflects the facts of the concept to be studied. Four metric factors were finally extracted by principal component analysis and maximum variance rotation, which were general performance, patient safety, team relationship, and emotion. It was consistent with the English version of the scale. The rotated factor loadings were all \u0026gt;\u0026thinsp;0.5 and there were no double-loading phenomena, meeting psychometric requirements. By validated factor analysis, CMIN/DF\u0026thinsp;\u0026lt;\u0026thinsp;3; GFI, TLI, IFI, and CFI were all \u0026gt;\u0026thinsp;0.9, and RMSEA was \u0026lt;\u0026thinsp;0.08.[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]The adjusted goodness-of-fit index (AGFI\u0026thinsp;=\u0026thinsp;0.857) did not meet the ideal fit criterion but was close to 0.9, which was still acceptable. Possibly due to the limitations of the sample size, the rest of the indicators met the ideal value rubric, and the model fit was satisfactory, suggesting good structural validity of the scale.\u003c/p\u003e \u003cp\u003eConvergent Validation is used to assess whether items measuring the same underlying constructs are grouped together, and the Chinese version of the SPS-N has CR values greater than 0.6 and AVE values greater than 0.5 for all four factors, indicating that the modified model has good intrinsic quality[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Therefore, the scale can be considered to have good convergent validity. When there is good discriminant validity between subscales, as indicated by the square root of the AVE being greater than the correlation coefficient for each individual subscale, the test of discriminant validity determines whether or not items with different constructs are classified together[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInternal consistency reliability refers to the homogeneity between all the questions that make up the test. Cronbach's α is less than 0.6, which is considered to be insufficient internal consistency; when it is between 0.7 and 0.8, there is a certain degree of reliability; and when it is between 0.8 and 0.9, it indicates a good degree of reliability[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].The Cronbach's α of the total scale in this study was 0.943, and the Cronbach's α of the dimensions were 0.843 to 0.944, indicating good homogeneity among the 21 items in the translated scale. Re-test reliability is used to reflect the stability and consistency of the test results of the same scale at different time points, and re-test reliability is expressed by the correlation coefficient r. r has a range of 0 to 1, and the closer it is to 1, the more reliable the retest is[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].The re-test reliability of this study was 0.896, and the re-test reliability of the dimensions ranged from 0.854 to 0.939, indicating good stability and consistency of the translated scales. Split-half reliability, the questionnaire entries are divided into two halves, which can be considered as two measurements in the shortest period of time, and the correlation coefficient between the two halves of the entries is calculated and used as the folded half reliability of the scale. When the Spearman correlation coefficient is ≧\u0026thinsp;0.7, it represents a good split-half reliability of the scale. The split-half reliability of this study was 0.750, indicating that the split-half reliability of the instrument was acceptable.\u003c/p\u003e \u003cp\u003eTo summaries, the Chinese SPS-N scale provides strong structural validity, content validity, and reliability, making it a trustworthy instrument for assessing the effects of presenteeism on nurse productivity and performance.\u003c/p\u003e"},{"header":"5 Limitations","content":"\u003cp\u003eDespite the methodological rigor of this study, there are some limitations. First, the survey was limited to a tertiary general hospital in Liaoning Province, China, using convenience sampling, which can limit the generalizability of the findings, so future studies could include more participants and validate the scale in different regions of China. Second, this study did not examine the association between the Chinese version of the SPS-N and other scales with similar conceptualizations, further validation of the relationship between other indicators related to nurse presenteeism is needed in the Chinese cultural context.\u003c/p\u003e"},{"header":"6 Conclusion","content":"\u003cp\u003eThe results of this study indicate that the Chinese version of the SPS-N scale has good psychometric properties in the Chinese cultural context. Nursing administrators can use the Chinese version of the SPS-N to assess the impact of presenteeism behaviors of nurses on the performance and productivity of nurses in their hospitals. At the same time, presenteeism is a public health issue of high importance in the fields of nursing management, mental health, and occupational health[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Nursing administrators should provide effective interventions to prevent clinical nurses from working while sick.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSPS-N Sickness Presenteeism Scale- Nurses \u0026nbsp;CMIN/DF chi-square/degree of freedom RMSEA Root-mean-square\u0026ensp;error\u0026ensp;of\u0026ensp;approximation CFI Comparative fit index \u0026nbsp;TLI Tucker lewis index \u0026nbsp;IFI Incremental fit index \u0026nbsp;GFI Goodness-of-fit index \u0026nbsp;AGFI Adjusted goodness-of-fit index \u0026nbsp;PGFI \u0026nbsp;Parsimony goodness-of-fit index \u0026nbsp;S-CVI Scale-level content validity index \u0026nbsp;I-CVI Item-level content validity index \u0026nbsp;KMO The Kaiser\u0026ndash;Meyer\u0026ndash;Olkin \u0026nbsp;EFA Exploratory factor analysis \u0026nbsp;CFA Confirmatory factor analysis \u0026nbsp;MI The modification indices \u0026nbsp;CR Critical ration \u0026nbsp;AVE Average variance extracted\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe express our great gratitude to the participants in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCL: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing-original draft, Writing-review \u0026amp; editing. LZ:Funding acquisition,Methodology,Project administration,Resources,Supervision, Visualization, Writing-review \u0026amp; editing. ZM: Investigation, Methodology, Resources.YL: Investigation, Methodology, Software.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe experimental data of this study are available from the authors upon request. Data will be provided by the authors upon reasonable request.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthics statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe studies involving humans were approved by Jinzhou Medical University\u0026rsquo;s Research Ethics Review Board. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSmith CM, Horne CE, Wei H: \u003cstrong\u003eNursing practice in modern healthcare environments: A systematic review of attributes, characteristics, and demonstrations\u003c/strong\u003e. \u003cem\u003eJ Adv Nurs \u003c/em\u003e2024.\u003c/li\u003e\n\u003cli\u003eLi Y, Guo B, Wang Y, Lv X, Li R, Guan X, Li L, Li J, Cao Y: \u003cstrong\u003eSerial-Multiple Mediation of Job Burnout and Fatigue in the Relationship Between Sickness Presenteeism and Productivity Loss in Nurses: A Multicenter Cross-Sectional Study\u003c/strong\u003e. \u003cem\u003eFront Public Health \u003c/em\u003e2021, \u003cstrong\u003e9\u003c/strong\u003e:812737.\u003c/li\u003e\n\u003cli\u003eAllemann A, Siebenh\u0026uuml;ner K, H\u0026auml;mmig O: \u003cstrong\u003ePredictors of Presenteeism Among Hospital Employees-A Cross-Sectional Questionnaire-Based Study in Switzerland\u003c/strong\u003e. \u003cem\u003eJ Occup Environ Med \u003c/em\u003e2019, \u003cstrong\u003e61\u003c/strong\u003e(12):1004-1010.\u003c/li\u003e\n\u003cli\u003eMin A, Kang M, Park H: \u003cstrong\u003eGlobal prevalence of presenteeism in the nursing workforce: A meta-analysis of 28 studies from 14 countries\u003c/strong\u003e. \u003cem\u003eJ Nurs Manag \u003c/em\u003e2022, \u003cstrong\u003e30\u003c/strong\u003e(7):2811-2824.\u003c/li\u003e\n\u003cli\u003eHomrich PHP, Dantas-Filho FF, Martins LL, Marcon ER: \u003cstrong\u003ePresenteeism among health care workers: literature review\u003c/strong\u003e. \u003cem\u003eRev Bras Med Trab \u003c/em\u003e2020, \u003cstrong\u003e18\u003c/strong\u003e(1):97-102.\u003c/li\u003e\n\u003cli\u003eRainbow JG, Drake DA, Steege LM: \u003cstrong\u003eNurse Health, Work Environment, Presenteeism and Patient Safety\u003c/strong\u003e. \u003cem\u003eWest J Nurs Res \u003c/em\u003e2020, \u003cstrong\u003e42\u003c/strong\u003e(5):332-339.\u003c/li\u003e\n\u003cli\u003eRainbow JG, Steege LM: \u003cstrong\u003ePresenteeism in nursing: An evolutionary concept analysis\u003c/strong\u003e. \u003cem\u003eNurs Outlook \u003c/em\u003e2017, \u003cstrong\u003e65\u003c/strong\u003e(5):615-623.\u003c/li\u003e\n\u003cli\u003eAysun K, Bayram Ş: \u003cstrong\u003eDetermining the level and cost of sickness presenteeism among hospital staff in Turkey\u003c/strong\u003e. \u003cem\u003eInt J Occup Saf Ergon \u003c/em\u003e2017, \u003cstrong\u003e23\u003c/strong\u003e(4):501-509.\u003c/li\u003e\n\u003cli\u003eUmann J, Guido Lde A, Grazziano Eda S: \u003cstrong\u003ePresenteeism in hospital nurses\u003c/strong\u003e. \u003cem\u003eRev Lat Am Enfermagem \u003c/em\u003e2012, \u003cstrong\u003e20\u003c/strong\u003e(1):159-166.\u003c/li\u003e\n\u003cli\u003eShan G, Wang S, Wang W, Guo S, Li Y: \u003cstrong\u003ePresenteeism in Nurses: Prevalence, Consequences, and Causes From the Perspectives of Nurses and Chief Nurses\u003c/strong\u003e. \u003cem\u003eFront Psychiatry \u003c/em\u003e2020, \u003cstrong\u003e11\u003c/strong\u003e:584040.\u003c/li\u003e\n\u003cli\u003eLetvak SA, Ruhm CJ, Gupta SN: \u003cstrong\u003eNurses\u0026apos; presenteeism and its effects on self-reported quality of care and costs\u003c/strong\u003e. \u003cem\u003eAm J Nurs \u003c/em\u003e2012, \u003cstrong\u003e112\u003c/strong\u003e(2):30-38; quiz 48, 39.\u003c/li\u003e\n\u003cli\u003eCicolini G, Della Pelle C, Cerratti F, Franza M, Flacco ME: \u003cstrong\u003eValidation of the Italian version of the Stanford Presenteeism Scale in nurses\u003c/strong\u003e. \u003cem\u003eJ Nurs Manag \u003c/em\u003e2016, \u003cstrong\u003e24\u003c/strong\u003e(5):598-604.\u003c/li\u003e\n\u003cli\u003eEndicott J, Nee J: \u003cstrong\u003eEndicott Work Productivity Scale (EWPS): a new measure to assess treatment effects\u003c/strong\u003e. \u003cem\u003ePsychopharmacol Bull \u003c/em\u003e1997, \u003cstrong\u003e33\u003c/strong\u003e(1):13-16.\u003c/li\u003e\n\u003cli\u003eOspina MB, Dennett L, Waye A, Jacobs P, Thompson AH: \u003cstrong\u003eA systematic review of measurement properties of instruments assessing presenteeism\u003c/strong\u003e. \u003cem\u003eAm J Manag Care \u003c/em\u003e2015, \u003cstrong\u003e21\u003c/strong\u003e(2):e171-185.\u003c/li\u003e\n\u003cli\u003eLu L, L. 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\u003c/em\u003e2023, \u003cstrong\u003e53\u003c/strong\u003e(11):594-600.\u003c/li\u003e\n\u003cli\u003eShao Y, Zhang H, Zhang X, Liang Q, Zhang H, Zhang F: \u003cstrong\u003eChinese version of exercise dependence scale-revised: psychometric analysis and exploration of risk factors\u003c/strong\u003e. \u003cem\u003eFront Psychol \u003c/em\u003e2023, \u003cstrong\u003e14\u003c/strong\u003e:1309205.\u003c/li\u003e\n\u003cli\u003eTong LK, Zhu MX, Wang SC, Cheong PL, Van IK: \u003cstrong\u003eA Chinese Version of the Caring Dimensions Inventory: Reliability and Validity Assessment\u003c/strong\u003e. \u003cem\u003eInt J Environ Res Public Health \u003c/em\u003e2021, \u003cstrong\u003e18\u003c/strong\u003e(13).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"nurses, reliability, validity, presenteeism, sickness","lastPublishedDoi":"10.21203/rs.3.rs-4694732/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4694732/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThere is a lack of an evaluation instrument to gauge how presenteeism practices affect nurses' productivity at work and the quality of the medical treatment they provide. The purpose of this study was to translate the Sickness Presenteeism Scale-Nurse (SPS-N) into the Chinese version of the SPS-N and to verify its reliability and validity in Chinese nurses.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe SPS-N was translated according to the Brislin translation model after authorization by the original author. A convenience sampling method was used and the reliability and validity of the scale were tested among 503 Chinese nurses.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe Cronbach's ɑ of the Chinese SPS-N was 0.924, and the content validity of the items ranged from 0.830 to 1.000. The four-factor exploratory factor model was used to explain 78.354% of the total variance. CMIN/DF\u0026thinsp;=\u0026thinsp;2.527, RMSEA\u0026thinsp;=\u0026thinsp;0.067, AGFI\u0026thinsp;=\u0026thinsp;0.857, TLI\u0026thinsp;=\u0026thinsp;0.941, IFI\u0026thinsp;=\u0026thinsp;0.950 ,CFI\u0026thinsp;=\u0026thinsp;0.949, GFI\u0026thinsp;=\u0026thinsp;0.900, and PGFI\u0026thinsp;=\u0026thinsp;0.692 were the model fit outcomes in the validation factor analysis. All of the model fit markers fell within reasonable bounds.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe reliability and validity of the Chinese version of the SPS-N can be used to evaluate the influence of nurses' presenteeism behavior on job performance. To inform nursing managers in developing programs and interventions to improve the performance of clinical nurses.\u003c/p\u003e","manuscriptTitle":"Cross-cultural adaptation and psychometric evaluation of the Chinese version of the Sickness Presenteeism Scale- Nurses:A cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-05 13:05:24","doi":"10.21203/rs.3.rs-4694732/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-26T07:03:46+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-28T13:48:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-19T08:46:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"139704866414582404159502577351449012537","date":"2024-11-18T23:54:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-15T13:00:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227490901512489996031957998821768878273","date":"2024-11-15T12:59:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-10-08T12:45:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"228341319151676305197588011518928510509","date":"2024-08-09T15:38:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"116190913386545303440846738307717979888","date":"2024-07-22T22:34:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-13T15:10:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-07-11T09:31:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-11T08:51:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nursing","date":"2024-07-06T02:56:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nursing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurs","sideBox":"Learn more about [BMC Nursing](http://bmcnurs.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurs/default.aspx","title":"BMC Nursing","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"daeda70b-0b67-4be0-bf96-ae4b686a5408","owner":[],"postedDate":"August 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-05-12T16:09:05+00:00","versionOfRecord":{"articleIdentity":"rs-4694732","link":"https://doi.org/10.1186/s12912-025-03113-w","journal":{"identity":"bmc-nursing","isVorOnly":false,"title":"BMC Nursing"},"publishedOn":"2025-05-07 15:57:48","publishedOnDateReadable":"May 7th, 2025"},"versionCreatedAt":"2024-08-05 13:05:24","video":"","vorDoi":"10.1186/s12912-025-03113-w","vorDoiUrl":"https://doi.org/10.1186/s12912-025-03113-w","workflowStages":[]},"version":"v1","identity":"rs-4694732","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4694732","identity":"rs-4694732","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}