Latent Profile Analysis of Core Competency in Intravenous Therapy Among Chinese Clinical Nurses: A Multicenter Cross-Sectional Study

Latent Profile Analysis of Core Competency in Intravenous Therapy Among Chinese Clinical Nurses: A Multicenter 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 Latent Profile Analysis of Core Competency in Intravenous Therapy Among Chinese Clinical Nurses: A Multicenter Cross-Sectional Study Li Song, Li Yuan, Qiqi Ye, Zhijia Zhang, Jiating Song, Daiyuan Huang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7251559/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Nov, 2025 Read the published version in BMC Nursing → Version 1 posted 10 You are reading this latest preprint version Abstract Background Nurses’ core competency in intravenous(IV) therapy directly impacts patient safety and treatment outcomes. This study aimed to identify latent classes of nurses’ intravenous therapy core competency using latent profile analysis (LPA) and explore key factors influencing these classes to inform targeted interventions. Methods A multicenter cross-sectional study was conducted from October 2023 to January 2024, involving 821 clinical nurses from 20 provincial-level regions in China. Data was collected using the validated Core Competency in Intravenous Therapy Scale. LPA was used to identify latent competency classes, and multivariate logistic regression was performed to explore risk factors. Results Three distinct latent classes were identified: (1) ‘Low-IV Core Competence’ (41.3%), with low scores across all dimensions; (2) ‘Moderate-IV Core Competence’ (45.9%), with medium scores across all dimensions; and (3) ‘High-IV Core Competence’ (12.8%), with high scores across all dimensions. Multivariate logistic regression showed that non-specialist nurses in intravenous therapy (Low vs. High: OR=42.362, p<0.001; Moderate vs. High: OR=45.829, p<0.001) and non-participation in intravenous therapy training programs (Low vs. High: OR=10.621, p<0.001; Moderate vs. High: OR=5.548, p<0.001) were strongly associated with lower competency. No significant associations were found with age, education level, hospital level, or work experience. Conclusions This study reveals a critical need for IV therapy core competency improvement in clinical nurses and underscore the importance of investments in IV specialist nurse development and standardized training to improve IV therapy quality and patient safety. Trial registration Not Applicable. Nurses Intravenous therapyNurses Intravenous therapy Core competence Latent profile analysis Risk factorsCore competence Latent profile analysis Risk factors Figures Figure 1 1 Background With the spread of peripherally inserted central catheter, midline catheters, and other advanced peripheral venous catheters, intravenous (IV) therapy applications span from acute resuscitation to chronic disease management, including chemotherapy and home parenteral nutrition[ 1 – 3 ]. By prolonging dwell time and enabling sustained infusion across hospital and community environments, these devices shorten length of hospital stays and enhance health-related quality of life [ 4 ]. Consequently, intravenous therapy is now the most frequently employed treatment method in clinical practice. However, the safe use of venous access devices (VADs) involves many aspects, such as venous assessment, device selection, insertion, and ongoing management, which require nursing staff to possess core competencies in IV therapy [ 3 , 5 ]. This ability is the foundation of safe intravenous therapy, because nurses’ core competency directly affects nursing quality and leads to a great impact on patient safety and clinical outcomes [ 6 , 7 ]. Nurses who acquire and maintain these abilities are crucial in promoting the wise use of VADs in clinical settings [ 8 ]. Therefore, healthcare institutions must attach importance to the cultivation of core competencies in IV therapy for nursing staff. However, there are significant gaps persisting in nurses’ IV therapy competencies. In a prospective audit of central venous catheter care bundles in an intensive care unit, reported adherence rates of 8% for documentation of dwell-time indication, 3% for aseptic handling technique, 15% for infusion-system integrity, and 17% for dressing management[ 9 ]. Concurrently, a tertiary-care study revealed that 52% of adult inpatients received peripheral intravenous catheters inserted over joint surfaces (antecubital fossa, dorsum of hand or wrist), only 19% had eight-hourly visual infusion phlebitis scores recorded, 14.4% exhibited local signs of phlebitis, and 44% were unaware of the catheter’s purpose[ 4 ]. These marked departures from evidence-based standards underscore the urgent need for targeted educational programs that enhance nurses’ IV therapy competence, reduce central line associated bloodstream infections and minimize the evidence to practice gap. At present, most interventions on the core competencies in intravenous therapy mainly focuses on IV knowledge and skill improving[ 10 – 13 ]. However, continual advances in both evidence and technology require these competencies to be regularly updated[ 14 ]. Core competence in the field of IV therapy not only incorporates both theory and practical skill, but also involve critical thinking, the ability to disseminate knowledge to colleagues, and the capacity to implement practice changes that align with Infusion Nurses Society standards [ 8 ]. According to Patricia Benner’s Novice-to-Expert Model, it reminds us of should create a clinical program to improve core competency in IV therapy based on the nurse’s individual-level differences. But most of our research has typically stratified IV-therapy competence using only global scores, thereby obscuring subgroup differences. Because distinct competency subgroups may be influenced by different determinants. Latent Profile Analysis (LPA), an individual-centered, model-based clustering technique, offers a more nuanced approach. By identifying homogeneous subpopulations on the basis of multiple observed indicators, LPA overcome traditional variable-centered methods that overlook individual variation[ 15 ]. Therefore, this study aims to address these gaps by identifying latent classes of nurses’ core competencies in IV therapy through LPA for designing precision interventions to address specific competency deficits. Therefore, the aim of the study was to explore the current study of intravenous therapy core competencies, identify subgroups of core competencies and examine influencing factors for different subgroups using LPA. 2 Methods 2.1 Study Design and Participants A multicenter cross-sectional study was conducted from October 2023 to January 2024, encompassing clinical nurses from 20 provincial-level administrative regions across China (Beijing, Gansu, Guangdong, Guangxi, Guizhou, Hainan, Henan, Heilongjiang, Hubei, Jilin, Jiangsu, Jiangxi, Shaanxi, Shanghai, Sichuan, Tianjin, Xinjiang, Yunnan, Zhejiang, and Chongqing). Participants were selected through stratified convenience sampling to ensure geographic representation. The eligibility criteria required: (1) registered nurse, (2) employee of the hospital investigated and (3) clinical practice at least 6 months. Exclusion criteria comprised: (1) nurses in internship or advanced training programs, and (2) those unavailable for survey participation due to leave or external academic engagements during the data collection period. 2.2 Measures 2.2.1 Demographic Information The demographic information questionnaire include four domains: (1) Institutional characteristics: hospital level; (2) Personal attributes: age, education level (high school or technical secondary, bachelor, master or higher), professional title (junior, intermediate, vice-senior, or senior), working experience( 10 years); (3) Specialist nurse in IV therapy (yes/no); (4) Continuing education: completion of accredited IV-related training programs within the preceding 3 years (verified through institutional training records). 2.2.2 Intravenous Therapy Competency Assessment Instrument The Core Competency in Intravenous Therapy Scale, originally developed by Wu et al.[ 16 ], comprises 28 items across five theoretically grounded dimensions: Professional Attitude(4 items), Relevant Theoretical Knowledge(7 items), Practical IV Skills(6 items), Critical Thinking & Clinical Judgement(6 items), and Professional Development Capacity(5 items). Utilizing a validated 5-point Likert scale (‘strongly disagree’ to ‘strongly agree’), total scores range from 28 to 140, with higher scores indicating superior competency in intravenous therapy. Psychometric evaluation demonstrated exceptional reliability (Cronbach’s α = 0.953 for the full scale; subscale α = 0.898–0.963) and established construct validity through confirmatory factor analysis (CFI = 0.968, RMSEA = 0.051), meeting rigorous standards for competency assessment in clinical nursing research. The scale development process followed COSMIN guidelines. Two Delphi rounds were conducted with 28 clinical experts (100% response). The expert authority coefficient was 0.98; Kendall’s W for consensus was 0.180 (Round 1) and 0.151 (Round 2), both P < 0.01. This instrument enables nurse managers to objectively benchmark staff competencies, informing targeted training program development. 2.3 Data collection and Quality Control This nationwide study was conducted under the academic supervision of the Gynecological Nursing Committee of the Chinese Nursing Association and the Obstetrical Nursing Committee of Guangdong Association of Integrated Traditional Chinese and Western Medicine, utilizing institutional partnerships with 46 member hospitals of the Guangdong Nurses Association. Data collection employed a secure web-based platform (Wenjuanxing, China's leading online survey system) with SSL encryption and IP address validation. Hospital nursing departments approved study participation after institutional review; QR codes with unique identifiers were distributed through nursing directors to unit managers, ensuring organizational-level control; Embedded validation checks included: Minimum response time threshold (> 120 seconds); Pattern detection algorithms for repetitive responses; Geolocation verification matching hospital IP ranges. From the initial 1,116 distributed questionnaires, 295 responses were excluded due to: Incomplete datasets (n = 127); Aberrant response patterns (n = 93); Geolocation inconsistencies (n = 75). The final analytical sample comprised 821 validated responses (73.57% validity rate), representing 20 provincial-level regions. 2.4 Statistical Analysis Descriptive analyses were conducted using the IBM SPSS 25.0 (SPSS Inc. Chicago, IL, USA) software, with categorical data presented as frequencies and percentages, normally distributed continuous data presented as mean ± standard deviation, and skewed data presented as interquartile range. Chi-square tests and Kruskal-Wallis non-parametric tests were used to examine differences in general data of clinical nurses across categories, and unordered multinomial logistic regression analysis was used for multivariate analysis. The significance level was set at α = 0.05. Latent profile analysis was performed using Mplus 8.3 to identify latent classes of nurses' intravenous therapy core competence. Model evaluation focused on several key metrics. Lower values of the Akaike information criterion (AIC), Bayesian information criterion (BIC), and adjusted Bayesian information criterion (aBIC) indicate better model fit. The Entropy index, ranging from 0 to 1, assesses classification accuracy, with values closer to 1 indicating more precise classification. The Lo-Mendell-Rubin (LMR) test and Bootstrapped likelihood ratio test (BLRT) evaluate model fit differences. A p-value < 0.05 suggests that a k-class model is superior to a k-1 class model[ 17 ]. 3 Results 3.1 Demographic Characteristics. A total of 821 clinical nurses were surveyed, including 200 from secondary hospitals (24.4%) and 621 from tertiary hospitals (75.6%). Of these, 407 (70.2%) had a bachelor's degree or above, and 264 (32.2%) were specialist nurses in IV therapy. 3.2 Score of core competency in IV therapy among nurses The overall IV therapy core competency score was (51.18±15.28), with a mean score of 1.83 for each item. Among the five dimensions, professional development scored highest (mean = 2.20) and professional attitude lowest (mean = 1.48). The mean score of the theoretical knowledge, critical thinking and IV therapy skill were between the other two dimensions (1.83, 1.82 and 1.76, respectively). 3.3 Latent profile analysis on the core competence of intravenous therapy for nurses Using the 28 items of the Core Competence Scale of Intravenous Therapy as indicators, Latent profile Models with 1 to 5 potential categories were fitted in sequence. As shown in Table 1, as the number of categories increased, the values of AIC, BIC, and aBIC decreased. The BIC value began to plateau at 3-class model. The 3-class model has a high entropy of 0.971, nearly identical to the 4-class model and slightly higher than the 2-class and 5-class models. The LMR values in 2-class model is significantly better than the 1-class model, but the 3-class model is not significantly better than the 2-class model. Similarly, higher-class models (4-class, 5-class) do not show significant improvement over their predecessors via LMR. The BLRT values were statistically significant for all models (P <0.05). Therefore, a three-category model was selected as the optimal model. 3.4 Characteristics and naming of the latent classes of core intravenous therapy competencies Based on Model 3, the distribution score of the three categories across the items of the core competence of intravenous therapy are shown in Figure 1. According to the score of each item, the three categories were named as follows: Class 1 had the lowest scores on all items of the core competence of intravenous therapy, including Professional Attitude, Theoretical Knowledge, IV Therapy Skills, Critical Thinking, and Professional Development. Thus, it was named ‘Low-IV Core Competence’, accounting for 41.3% (339/821). Class 2 showed medium level of scores on all items. It was named the ‘Moderate-IV Core Competence’, representing 45.9% (377/821) of the sample. Class 3 presented the highest scores on all items. This category was named the ‘High-IV Core Competence’ and accounted for 12.8% (105/821) of the sample. 3.5 Univariate Analysis of Factors Influencing Core Competencies in Intravenous Therapy The results of univariate analysis of influencing factors for the latent classes of clinical nurses' core intravenous therapy competencies are shown in Table 2. There were statistically significant differences in professional titles, specialist nurses in IV therapy, and completion of accredited IV-related training programs between the three categories of nurses (P<0.05). However, there were no statistically significant differences in hospital level, age, or educational level in the distribution of latent classes of clinical nurses' core intravenous therapy competencies (P <0.05). Table 2. Univariate Analysis of Core Competencies in Intravenous Therapy Class Low-IV Core Competence (n=339) Middle-IV Core Competence （ n=377 ） High-IV Core Competence （ n=105 ） χ 2 /Fisher P Hospital Level 4.286 a 0.117 secondary 72(21.2%) 97(25.7%) 32(30.5%) tertiary 267(78.8%) 280(74.3%) 73(69.5%) Age 10.413 a 0.108 18-25 32(9.4%) 50(13.3%) 16(15.2%) 25-30 82(24.2%) 108(28.6%) 30(28.6%) 30-35 76(22.4%) 85(22.5%) 27(25.7%) >35 149(44.0%) 134(35.5%) 32(30.5%) Education level 1.839 b 0.764 ≤Junior college 96(28.3%) 114(30.2%) 35(33.3%) Undergraduate 241(71.1%) 259(68.7%) 69(65.7%) Postgraduate 2(0.6%) 4(1.1%) 1(1.0%) Professional title 15.137 a 0.004 Nurse 43(12.7%) 52(13.8%) 25(23.8%) Senior nurse 114(33.6%) 152(40.3%) 42(40.0%) Supervisor nurse or above 182(53.7%) 173(45.9%) 38(36.2%) Work experiences 13.481 a 0.009 10 years 214(63.1%) 197(52.3%) 50(47.6%) Specialist nurse in IV therapy 53.048 a <0.001 Yes 205(60.5%) 249(66.0%) 103(98.1%) No 134(39.5%) 128(34.0%) 2(1.9%) IV training programs 82.316 a <0.001 Yes 11(3.2%) 24(6.4%) 32(30.5%) No 328(96.8%) 353(93.6%) 73(69.5%) Note. a-χ 2 ; b-Fisher 3.6 Multivariable Logistic Regression Analysis of Core Competencies in Intravenous Therapy The multivariable logistic regression results are presented in Table 3. The profiles of IV therapy core competency served as the dependent variable, with the ‘high IV therapy core competency group’ as the reference. Demographic information, specialist nurses in IV therapy, and whether they had received intravenous therapy-related training served as independent factors. The results showed that specialist nurse in IV Therapy (OR=42.36, 95%CI: 9.72-184.70, p<0.001)(OR=45.83, 95%CI: 10.51-199.79,p<0.001) and IV Training Programs (OR=10.62, 95%CI:4.92-22.95, p <0.001)(OR=5.55, 95%CI: 2.94-10.46, p <0.001) were strongly associated with lower IV therapy core competency levels. Table 3. Multivariate Logistic Regression Analysis of IV Therapy Core Competencies Variable Low IV core competency group (ref. high IV core competency) Moderate IV core competency group (ref. high IV core competency group) β SE OR P 95%CI β SE OR P 95%CI Lower Upper Lower Upper Age (ref. >35) 18-25 1.047 0.808 2.848 0.195 0.585 13.877 1.199 0.785 3.318 0.126 0.713 15.446 25-30 0.864 0.612 2.372 0.158 0.714 7.878 0.761 0.604 2.140 0.208 0.655 6.991 30-35 0.113 0.417 1.119 0.787 0.494 2.536 0.192 0.415 1.212 0.643 0.537 2.736 Hospital Level (ref. tertiary) secondary -0.318 0.285 0.728 0.264 0.416 1.272 0.021 0.276 1.021 0.939 0.595 1.755 Education level (ref. Postgraduate) ≤Junior college 0.730 1.470 2.076 0.619 0.117 36.987 0.131 1.347 1.140 0.922 0.081 15.972 Undergraduate 0.634 1.460 1.885 0.664 0.108 32.933 0.028 1.339 1.028 0.984 0.075 14.184 Work experiences (ref. >10 years) <5 years -0.966 0.620 0.381 0.119 0.113 1.283 0.014 0.597 1.014 0.982 0.314 3.268 6-10 years -0.530 0.460 0.588 0.248 0.239 1.448 -0.145 0.450 0.865 0.747 0.358 2.089 Professional title (ref. Supervisor nurse or above) Nurse 0.390 0.592 1.478 0.510 0.463 4.714 -0.260 0.581 0.771 0.654 0.247 2.406 Senior nurse 0.667 0.419 1.948 0.111 0.857 4.429 0.674 0.413 1.962 0.102 0.874 4.405 Specialist nurse in IV therapy (ref. yes) No 3.746 0.751 42.362 <0.001 9.716 184.704 3.825 0.751 45.829 <0.001 10.512 199.794 IV training programs (ref. yes) No 2.363 0.393 10.621 <0.001 4.916 22.945 1.714 0.323 5.548 <0.001 2.944 10.459 Abbreviations: CI, confidence interval; OR, odds-ratio. 4 Discussion To our knowledge, this is the first study to explore clusters of nurses’ core competency in IV therapy. This study used LPA to reveal significant heterogeneity in clinical nurses of IV therapy core competency, identifying three categories: ‘High IV Competence’, ‘Moderate IV Competence’ and ‘Low IV Competence’. In this study, nearly half of nurses in the moderate group (45.9%) and over two-fifths in the low group (41.3%), while only 12.8% achieved high competency, which highlights a critical need for targeted improvement. Notably, all three profiles showed consistent relative performance across the five competency dimensions: professional development scored highest (mean=2.20), while professional attitude scored lowest (mean=1.48), with theoretical knowledge, critical thinking, and IV therapy skills in between. This dimension-specific variability offers insights into how competency is prioritized in nursing practice. The strength in professional development reflects clinical teaching, and research innovation abilities which may be because IV therapy core competency represents a critical determinant of IV therapy quality and the specialized skills needed for effective intravenous treatments[18]. As IV technology advances, clinical nurses need not only practical skills but also stronger learning, teaching, and research innovation abilities for professional development. Modern nursing education frameworks increasingly prioritize lifelong learning, requiring nurses to engage in ongoing professional development to maintain licensure and adapt to evolving clinical guidelines[19]. Many healthcare institutions now mandate or incentivize participation in workshops, certifications, and teaching activities related to IV therapy (e.g., training new staff), which directly strengthens skills in clinical teaching and reflective practice. In contrast, the weakness in professional attitude encompassing patient communication, empathy, or safety mindfulness raises concerns, as attitude directly impacts patient satisfaction and adherence to care protocols. Possible drivers include time constraints from high workloads, which prioritize technical efficiency over interpersonal care, or curricula that overemphasize technical skills at the expense of attitude. Nurses in the ‘High-IV’ group excel not only in technical skills but also in attitude and critical thinking, indicating that competency is shaped by systemic factors rather than isolated skill deficits[20], underlying enablers (e.g., access to training, mentorship, or organizational support) may foster holistic proficiency. The lack of specialist certification in IV therapy and non-participation in IV training programs were strongly and significantly associated with lower competency levels (low or moderate vs. high). In contrast, demographic variables (age, education) and professional factors (work experience, hospital level) showed no significant associations with IV core competency. These findings are consistent with previous research emphasizing the role of specialized training in enhancing clinical skills, which found that targeted training programs improve proficiency in IV catheter insertion and complication management[21, 22]. Our results further reinforce that formal training programs beyond general professional experience are critical for developing high-level IV competency. Notably, the lack of association between work experience and competency contrasts with a few earlier studies [23, 24], which may reflect differences in how 'experience' was operationalized (e.g., years in practice vs. hours of IV-specific practice). The strong association between specialist certification/training and higher competency likely reflects the structured, skill-specific content of these programs, which focus on evidence-based practices, advanced techniques, and error prevention areas critical for IV therapy safety and effectiveness. The non-significant associations with age, education, or work experience suggest that competency in IV therapy is not merely a function of general professional maturity but requires targeted skill development. This may explain why even experienced providers without specialized training showed no advantage in competency levels[25]. Practically, these findings underscore the need for healthcare institutions to prioritize IV therapy training programs and incentivize specialist certification. Standardizing access to such training could help reduce variability in competency and improve patient outcomes, as low IV competency is linked to higher rates of infiltration, infection, and patient discomfort[26]. Theoretically, our results support the construct of 'competency as skill-specific' rather than a byproduct of general professional development, challenging assumptions that experience alone drives clinical proficiency. 4.1 Strength and Limitations This study has several strengths. First, the use of LPA allowed for the identification of naturally occurring competency subgroups, offering a more nuanced understanding than traditional aggregate scoring methods. Second, the large sample size (n=821) enhances the generalizability of the latent profiles and regression findings. Third, the multivariate logistic regression adjusted for multiple potential confounders, strengthening causal inference regarding the role of training and certification. Meanwhile, several limitations should be acknowledged. First, the cross-sectional design precludes conclusions about causality; for example, while training participation correlates with higher competency, we cannot definitively conclude that training causes improved performance (reverse causality, e.g., more competent nurses may seek out training, cannot be ruled out). Second, competency was assessed via self-reported questionnaires, which may be subject to response bias. Future studies could incorporate objective skill assessments to validate self-reported scores. Third, unmeasured variables such as institutional support for training, mentorship availability, or workload stress may also influence competency and were not included in the regression model. Finally, the sample was drawn from 20 provincial regions, while geographic distribution disparities existed (Guangdong 87.2%). 5 Conclusions This study uses LPA to identify three distinct IV therapy competency profiles among nurses, in which only 12.8% achieved high competency. This reminds us of a critical need for IV therapy core competency improvement in clinical nurses. Furthermore, we find specialized certification and continuous training are pivotal to enhancing nurses’ IV therapy core competency, while traditional demographic and professional factors play a limited role, which underscore the urgency of targeted interventions to address IV therapy competency gaps, the need to prioritize specialist nurses’ development and mandatory continuous training in IV therapy. Firstly, hospitals should establish structured certification programs for IV specialists, ensuring they receive advanced training in complex procedures (e.g., central line insertion, managing difficult venous access) and serve as mentors for general nurses. Secondly, competency assessment should focus on skill-based evaluations rather than proxy measures like tenure or degree. Additionally, standardized, evidence-based training in IV therapy are essential. With consistent access to this training, even nurses in secondary hospitals or those with limited experience can achieve high competency. Nursing managers should conduct regular competency audits that include simulation-based assessments of intravenous techniques and complication management, enabling precise identification of gaps and targeted interventions to enhance the quality of IV therapy and patient safety. Abbreviations IV: Intravenous. LPA: Latent profile analysis. VADs: Venous access devices. AIC: Akaike information criterion. BIC: Bayesian information criterion. aBIC: adjusted Bayesian information criterion. LMR: Lo-Mendell-Rubin. BLRT: Bootstrapped likelihood ratio test. CI: Confidence interval. OR: Odds-ratio. Declarations Ethics approval and consent to participate The study was reviewed and approved by the Research Ethics Committee of the Second Affiliated Hospital of Guangzhou University of Chinese Medicine (approval no. BE2020-045-01). The study protocol conformed to the Declaration of Helsinki, with voluntary participation and electronic informed consent obtained prior to survey access.The initial page of the questionnaire, provided comprehensive information on the study’s aims, procedures, and ethical safeguards. Participants were assured that their data would remain confidential and anonymous. Consent for publication Not applicable. Availability of data and materials The data supporting the findings of this study are available on request from the corresponding author. The data is not publicly available due to privacy or ethical restrictions. Conflict of Interest The authors declare no conflicts of interest. Funding This research was conducted with the support of Guangdong Nurses Association (NO. P2023035). Authors’ contributions Study conception and design: LS, QHH, JTS; Data collection: DYH, QQY, LY, ZJZ; Data analysis and interpretation: LS, ZJZ, LY; Drafting of the article: LS, YL. 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Walsh IK, Dounavi K, Houghton J, Cullen KM, Dillenburger K: Fluency training in medical education: Improving competence in IV fluid therapy knowledge and skills . MedEdPublish (2016) 2019, 8 :23. Stuckey C, Curtis MP: Development of a nurse-led ultrasound-guided peripheral intravenous program . Journal of vascular nursing : official publication of the Society for Peripheral Vascular Nursing 2019, 37 (4):246-249. Indarwati F, Munday J, Keogh S: Nurse knowledge and confidence on peripheral intravenous catheter insertion and maintenance in pediatric patients: A multicentre cross-sectional study . Journal of pediatric nursing 2022, 62 :10-16. Cruz JP, Baigulina B, Shalkenova Z, Tau G, Dossymbayeva E, Kostauletova A: Investigating the Kazakhstani Pediatric Nurses' intravenous catheter management knowledge and confidence: A cross-sectional study . Nurse education in practice 2023, 73 :103816. Yilmaz DU, Yilmaz D, Karaman D: Clinical nurses' knowledge and practices on routine care related to the prevention of complications of peripheral intravenous therapy: A cross-sectional study . The journal of vascular access 2023, 24 (2):277-283. Hulse AL: Clinical competency assessment in intravenous therapy and vascular access: part 1 . British journal of nursing (Mark Allen Publishing) 2013, 22 (16):933-934, 936-937. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFile1.QuestionnaireEnglish.pdf SupplementaryFile2.EthicsApproval.pdf SupplementaryFile3.InformedConsent.pdf Cite Share Download PDF Status: Published Journal Publication published 05 Nov, 2025 Read the published version in BMC Nursing → Version 1 posted Editorial decision: Revision requested 19 Sep, 2025 Reviews received at journal 18 Sep, 2025 Reviews received at journal 12 Sep, 2025 Reviewers agreed at journal 02 Sep, 2025 Reviewers agreed at journal 25 Aug, 2025 Reviewers invited by journal 25 Aug, 2025 Editor assigned by journal 25 Aug, 2025 Editor invited by journal 12 Aug, 2025 Submission checks completed at journal 07 Aug, 2025 First submitted to journal 07 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Zhuhai","correspondingAuthor":false,"prefix":"","firstName":"Jiating","middleName":"","lastName":"Song","suffix":""},{"id":508373484,"identity":"7697e2c5-722a-4dfa-82e3-fff304210102","order_by":5,"name":"Daiyuan Huang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Guangzhou University of Chinese Medicine GUANGZHOU","correspondingAuthor":false,"prefix":"","firstName":"Daiyuan","middleName":"","lastName":"Huang","suffix":""},{"id":508373485,"identity":"27deb7cd-9230-41b6-964f-c9549e44b5fa","order_by":6,"name":"Xi Wen","email":"","orcid":"","institution":"The Second Affiliated Hospital of Guangzhou University of Chinese Medicine GUANGZHOU","correspondingAuthor":false,"prefix":"","firstName":"Xi","middleName":"","lastName":"Wen","suffix":""},{"id":508373486,"identity":"9a6215b1-d776-449c-878a-8c1f560fa9c9","order_by":7,"name":"Qihua Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIie3Rra7CMBTA8UOWVHXMFrO9wsjsHuY0JHUkSOQE6cS9BAtvgUR2HFs8AjFCMj0MCYYwsPeG7ror+lNH9J9+AXjeP8SiVWtwnnOW1LLuBncyFGZsWqviIeAlra1yJzFgVm0WlMUgm9FZ73scDAxSWCipgdQcmYGo/MLPSVAYCne51AOtjshPIOxh69ilKii03S4B7xLRQCqmrmQCFGqSmkW3GabUJ1FQbTRljHcTYp9EWHg/MhMwEWgUd94lWX0H7esrkzXI6/2Rx1G5/Jz8wP+23PM8z/vVE8llT4znEF7rAAAAAElFTkSuQmCC","orcid":"","institution":"The Second Affiliated Hospital of Guangzhou University of Chinese Medicine GUANGZHOU","correspondingAuthor":true,"prefix":"","firstName":"Qihua","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2025-07-30 10:08:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7251559/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7251559/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12912-025-04007-7","type":"published","date":"2025-11-05T15:57:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90464822,"identity":"a6943fcf-83aa-4480-a2ff-9b27610f7b91","added_by":"auto","created_at":"2025-09-03 05:11:58","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":34138,"visible":true,"origin":"","legend":"\u003cp\u003eProfiles of IV Therapy Competency Among Clinical Nurses\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7251559/v1/54e049d5193f39669ab2399b.png"},{"id":95564585,"identity":"63683e8d-a989-4a92-89ab-a3c271a0e485","added_by":"auto","created_at":"2025-11-10 16:10:05","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2539627,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7251559/v1/539784d4-e54c-4658-b615-913859ecbe0b.pdf"},{"id":90464824,"identity":"e75d690a-589c-4406-8be1-2faddc57ff51","added_by":"auto","created_at":"2025-09-03 05:11:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":101073,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.QuestionnaireEnglish.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7251559/v1/2bffaf86432a608904160319.pdf"},{"id":90464828,"identity":"bcf9b2f0-1d07-456b-a0da-c83a24d4beae","added_by":"auto","created_at":"2025-09-03 05:11:58","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":602988,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile2.EthicsApproval.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7251559/v1/57331129b440819c86cfa0c7.pdf"},{"id":90464825,"identity":"eb818f43-d451-471a-8b9d-1182d8c1b07e","added_by":"auto","created_at":"2025-09-03 05:11:58","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":92602,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile3.InformedConsent.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7251559/v1/6a828d8fcfee4459f37f262a.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Latent Profile Analysis of Core Competency in Intravenous Therapy Among Chinese Clinical Nurses: A Multicenter Cross-Sectional Study","fulltext":[{"header":"1 Background","content":"\u003cp\u003eWith the spread of peripherally inserted central catheter, midline catheters, and other advanced peripheral venous catheters, intravenous (IV) therapy applications span from acute resuscitation to chronic disease management, including chemotherapy and home parenteral nutrition[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. By prolonging dwell time and enabling sustained infusion across hospital and community environments, these devices shorten length of hospital stays and enhance health-related quality of life [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Consequently, intravenous therapy is now the most frequently employed treatment method in clinical practice. However, the safe use of venous access devices (VADs) involves many aspects, such as venous assessment, device selection, insertion, and ongoing management, which require nursing staff to possess core competencies in IV therapy [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This ability is the foundation of safe intravenous therapy, because nurses\u0026rsquo; core competency directly affects nursing quality and leads to a great impact on patient safety and clinical outcomes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Nurses who acquire and maintain these abilities are crucial in promoting the wise use of VADs in clinical settings [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, healthcare institutions must attach importance to the cultivation of core competencies in IV therapy for nursing staff.\u003c/p\u003e\u003cp\u003eHowever, there are significant gaps persisting in nurses\u0026rsquo; IV therapy competencies. In a prospective audit of central venous catheter care bundles in an intensive care unit, reported adherence rates of 8% for documentation of dwell-time indication, 3% for aseptic handling technique, 15% for infusion-system integrity, and 17% for dressing management[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Concurrently, a tertiary-care study revealed that 52% of adult inpatients received peripheral intravenous catheters inserted over joint surfaces (antecubital fossa, dorsum of hand or wrist), only 19% had eight-hourly visual infusion phlebitis scores recorded, 14.4% exhibited local signs of phlebitis, and 44% were unaware of the catheter\u0026rsquo;s purpose[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These marked departures from evidence-based standards underscore the urgent need for targeted educational programs that enhance nurses\u0026rsquo; IV therapy competence, reduce central line associated bloodstream infections and minimize the evidence to practice gap.\u003c/p\u003e\u003cp\u003eAt present, most interventions on the core competencies in intravenous therapy mainly focuses on IV knowledge and skill improving[\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, continual advances in both evidence and technology require these competencies to be regularly updated[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Core competence in the field of IV therapy not only incorporates both theory and practical skill, but also involve critical thinking, the ability to disseminate knowledge to colleagues, and the capacity to implement practice changes that align with Infusion Nurses Society standards [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. According to Patricia Benner\u0026rsquo;s Novice-to-Expert Model, it reminds us of should create a clinical program to improve core competency in IV therapy based on the nurse\u0026rsquo;s individual-level differences. But most of our research has typically stratified IV-therapy competence using only global scores, thereby obscuring subgroup differences. Because distinct competency subgroups may be influenced by different determinants. Latent Profile Analysis (LPA), an individual-centered, model-based clustering technique, offers a more nuanced approach. By identifying homogeneous subpopulations on the basis of multiple observed indicators, LPA overcome traditional variable-centered methods that overlook individual variation[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTherefore, this study aims to address these gaps by identifying latent classes of nurses\u0026rsquo; core competencies in IV therapy through LPA for designing precision interventions to address specific competency deficits. Therefore, the aim of the study was to explore the current study of intravenous therapy core competencies, identify subgroups of core competencies and examine influencing factors for different subgroups using LPA.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Design and Participants\u003c/h2\u003e\u003cp\u003eA multicenter cross-sectional study was conducted from October 2023 to January 2024, encompassing clinical nurses from 20 provincial-level administrative regions across China (Beijing, Gansu, Guangdong, Guangxi, Guizhou, Hainan, Henan, Heilongjiang, Hubei, Jilin, Jiangsu, Jiangxi, Shaanxi, Shanghai, Sichuan, Tianjin, Xinjiang, Yunnan, Zhejiang, and Chongqing). Participants were selected through stratified convenience sampling to ensure geographic representation. The eligibility criteria required: (1) registered nurse, (2) employee of the hospital investigated and (3) clinical practice at least 6 months. Exclusion criteria comprised: (1) nurses in internship or advanced training programs, and (2) those unavailable for survey participation due to leave or external academic engagements during the data collection period.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Measures\u003c/h2\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 Demographic Information\u003c/h2\u003e\u003cp\u003eThe demographic information questionnaire include four domains: (1) Institutional characteristics: hospital level; (2) Personal attributes: age, education level (high school or technical secondary, bachelor, master or higher), professional title (junior, intermediate, vice-senior, or senior), working experience(\u0026lt;\u0026thinsp;5 years, 6\u0026ndash;10 years and \u0026gt;\u0026thinsp;10 years); (3) Specialist nurse in IV therapy (yes/no); (4) Continuing education: completion of accredited IV-related training programs within the preceding 3 years (verified through institutional training records).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Intravenous Therapy Competency Assessment Instrument\u003c/h2\u003e\u003cp\u003eThe Core Competency in Intravenous Therapy Scale, originally developed by Wu et al.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], comprises 28 items across five theoretically grounded dimensions: Professional Attitude(4 items), Relevant Theoretical Knowledge(7 items), Practical IV Skills(6 items), Critical Thinking \u0026amp; Clinical Judgement(6 items), and Professional Development Capacity(5 items). Utilizing a validated 5-point Likert scale (\u0026lsquo;strongly disagree\u0026rsquo; to \u0026lsquo;strongly agree\u0026rsquo;), total scores range from 28 to 140, with higher scores indicating superior competency in intravenous therapy. Psychometric evaluation demonstrated exceptional reliability (Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.953 for the full scale; subscale α\u0026thinsp;=\u0026thinsp;0.898\u0026ndash;0.963) and established construct validity through confirmatory factor analysis (CFI\u0026thinsp;=\u0026thinsp;0.968, RMSEA\u0026thinsp;=\u0026thinsp;0.051), meeting rigorous standards for competency assessment in clinical nursing research. The scale development process followed COSMIN guidelines. Two Delphi rounds were conducted with 28 clinical experts (100% response). The expert authority coefficient was 0.98; Kendall\u0026rsquo;s W for consensus was 0.180 (Round 1) and 0.151 (Round 2), both \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01. This instrument enables nurse managers to objectively benchmark staff competencies, informing targeted training program development.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Data collection and Quality Control\u003c/h2\u003e\u003cp\u003e This nationwide study was conducted under the academic supervision of the Gynecological Nursing Committee of the Chinese Nursing Association and the Obstetrical Nursing Committee of Guangdong Association of Integrated Traditional Chinese and Western Medicine, utilizing institutional partnerships with 46 member hospitals of the Guangdong Nurses Association. Data collection employed a secure web-based platform (Wenjuanxing, China's leading online survey system) with SSL encryption and IP address validation. Hospital nursing departments approved study participation after institutional review; QR codes with unique identifiers were distributed through nursing directors to unit managers, ensuring organizational-level control; Embedded validation checks included: Minimum response time threshold (\u0026gt;\u0026thinsp;120 seconds); Pattern detection algorithms for repetitive responses; Geolocation verification matching hospital IP ranges. From the initial 1,116 distributed questionnaires, 295 responses were excluded due to: Incomplete datasets (n\u0026thinsp;=\u0026thinsp;127); Aberrant response patterns (n\u0026thinsp;=\u0026thinsp;93); Geolocation inconsistencies (n\u0026thinsp;=\u0026thinsp;75). The final analytical sample comprised 821 validated responses (73.57% validity rate), representing 20 provincial-level regions.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e\u003cp\u003eDescriptive analyses were conducted using the IBM SPSS 25.0 (SPSS Inc. Chicago, IL, USA) software, with categorical data presented as frequencies and percentages, normally distributed continuous data presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and skewed data presented as interquartile range. Chi-square tests and Kruskal-Wallis non-parametric tests were used to examine differences in general data of clinical nurses across categories, and unordered multinomial logistic regression analysis was used for multivariate analysis. The significance level was set at α\u0026thinsp;=\u0026thinsp;0.05. Latent profile analysis was performed using Mplus 8.3 to identify latent classes of nurses' intravenous therapy core competence. Model evaluation focused on several key metrics. Lower values of the Akaike information criterion (AIC), Bayesian information criterion (BIC), and adjusted Bayesian information criterion (aBIC) indicate better model fit. The Entropy index, ranging from 0 to 1, assesses classification accuracy, with values closer to 1 indicating more precise classification. The Lo-Mendell-Rubin (LMR) test and Bootstrapped likelihood ratio test (BLRT) evaluate model fit differences. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 suggests that a k-class model is superior to a k-1 class model[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"3 Results","content":"\u003cp\u003e\u003cstrong\u003e3.1 Demographic Characteristics.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 821 clinical nurses were surveyed, including 200 from secondary hospitals (24.4%) and 621 from tertiary hospitals (75.6%). Of these, 407 (70.2%) had a bachelor\u0026apos;s degree or above, and 264 (32.2%) were specialist nurses in IV therapy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Score of core competency in IV therapy among nurses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe overall IV therapy core competency score was (51.18\u0026plusmn;15.28), with a mean score of 1.83 for each item. Among the five dimensions, professional development scored highest (mean = 2.20) and professional attitude lowest (mean = 1.48). The mean score of the theoretical knowledge, critical thinking and IV therapy skill were between the other two dimensions (1.83, 1.82 and 1.76, respectively).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Latent profile analysis on the core competence of intravenous therapy for nurses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing the 28 items of the Core Competence Scale of Intravenous Therapy as indicators, Latent profile Models with 1 to 5 potential categories were fitted in sequence. As shown in Table 1, as the number of categories increased, the values of AIC, BIC, and aBIC decreased. The BIC value began to plateau at 3-class model. The 3-class model has a high entropy of 0.971, nearly identical to the 4-class model and slightly higher than the 2-class and 5-class models. The LMR values in 2-class model is significantly better than the 1-class model, but the 3-class model is not significantly better than the 2-class model. Similarly, higher-class models (4-class, 5-class) do not show significant improvement over their predecessors via LMR. The BLRT values were statistically significant for all models (P \u0026lt;0.05). Therefore, a three-category model was selected as the optimal model.\u003c/p\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Characteristics and naming of the latent classes of core intravenous therapy competencies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on Model 3, the distribution score of the three categories across the items of the core competence of intravenous therapy are shown in Figure 1. According to the score of each item, the three categories were named as follows: Class 1 had the lowest scores on all items of the core competence of intravenous therapy, including Professional Attitude, Theoretical Knowledge, IV Therapy Skills, Critical Thinking, and Professional Development. Thus, it was named \u0026lsquo;Low-IV Core Competence\u0026rsquo;, accounting for 41.3% (339/821). Class 2 showed medium level of scores on all items. It was named the \u0026lsquo;Moderate-IV Core Competence\u0026rsquo;, representing 45.9% (377/821) of the sample. Class 3 presented the highest scores on all items. This category was named the \u0026lsquo;High-IV Core Competence\u0026rsquo; and accounted for 12.8% (105/821) of the sample.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Univariate Analysis of Factors Influencing Core Competencies in Intravenous Therapy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of univariate analysis of influencing factors for the latent classes of clinical nurses\u0026apos; core intravenous therapy competencies are shown in Table 2. There were statistically significant differences in professional titles, specialist nurses in IV therapy, and completion of accredited IV-related training programs between the three categories of nurses (P\u0026lt;0.05). However, there were no statistically significant differences in hospital level, age, or educational level in the distribution of latent classes of clinical nurses\u0026apos; core intravenous therapy competencies (P \u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eTable 2. Univariate Analysis of Core Competencies in Intravenous Therapy\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClass\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow-IV Core Competence\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n=339)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMiddle-IV Core Competence\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003en=377\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh-IV Core Competence\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003en=105\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026chi;\u003csup\u003e2\u003c/sup\u003e/Fisher\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e4.286\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003esecondary\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e72(21.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e97(25.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e32(30.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003etertiary\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e267(78.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e280(74.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e73(69.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e10.413\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18-25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e32(9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e50(13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e16(15.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25-30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e82(24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e108(28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e30(28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30-35\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e76(22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e85(22.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e27(25.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;35\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e149(44.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e134(35.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e32(30.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e1.839\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.764\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026le;Junior college\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e96(28.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e114(30.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e35(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUndergraduate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e241(71.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e259(68.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e69(65.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePostgraduate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e2(0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e4(1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e1(1.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional title\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e15.137\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNurse\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e43(12.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e52(13.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e25(23.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSenior nurse\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e114(33.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e152(40.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e42(40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSupervisor nurse or above\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e182(53.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e173(45.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e38(36.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWork experiences\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e13.481\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;5 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e55(16.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e91(24.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e28(26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6-10 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e70(20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e89(23.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e27(25.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt;10 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e214(63.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e197(52.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e50(47.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecialist nurse in IV therapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e53.048\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e205(60.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e249(66.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e103(98.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e134(39.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e128(34.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e2(1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIV training programs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e82.316\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e11(3.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e24(6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e32(30.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\n \u003cp\u003e328(96.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e353(93.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e73(69.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\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\n\u003cp\u003eNote. a-\u0026chi;\u003csup\u003e2\u003c/sup\u003e; b-Fisher\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 Multivariable Logistic Regression Analysis of Core Competencies in Intravenous Therapy\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe multivariable logistic regression results are presented in Table 3. The profiles of IV therapy core competency served as the dependent variable, with the \u0026lsquo;high IV therapy core competency group\u0026rsquo; as the reference. Demographic information, specialist nurses in IV therapy, and whether they had received intravenous therapy-related training served as independent factors. The results showed that specialist nurse in IV Therapy (OR=42.36, 95%CI: 9.72-184.70, p\u0026lt;0.001)(OR=45.83, 95%CI: 10.51-199.79,p\u0026lt;0.001) and IV Training Programs (OR=10.62, 95%CI:4.92-22.95, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001)(OR=5.55, 95%CI: 2.94-10.46, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001) were strongly associated with lower IV therapy core competency levels.\u003c/p\u003e\n\u003cp\u003eTable 3. Multivariate Logistic Regression Analysis of IV Therapy Core Competencies\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"left\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 40px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow IV core competency group (ref. high IV core competency)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"6\" style=\"width: 47px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate IV core competency group (ref. high IV core competency group)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 6px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 6px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 6px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 7px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 14px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 6px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 7px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 8px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 17px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003eUpper\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003eLower\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003eUpper\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (ref. \u0026gt;35)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e18-25\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.047\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e2.848\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.585\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e13.877\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.785\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e3.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.713\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e15.446\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25-30\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.864\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.612\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e2.372\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e7.878\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.655\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e6.991\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30-35\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.417\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.494\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2.536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.192\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.643\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2.736\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Level (ref. tertiary)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003esecondary\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.728\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.264\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.416\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.939\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e1.755\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level (ref. Postgraduate)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026le;Junior college\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.730\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.470\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e2.076\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e36.987\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.922\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e15.972\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUndergraduate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.634\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e32.933\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.339\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e14.184\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWork experiences (ref. \u0026gt;10 years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;5 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.620\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.283\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.982\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.314\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e3.268\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6-10 years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-0.530\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.450\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.865\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2.089\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessional title (ref. Supervisor nurse or above)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNurse\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.390\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.592\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.478\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.510\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.463\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e4.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.771\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.654\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.247\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e2.406\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSenior nurse\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e4.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.674\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.413\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e4.405\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecialist nurse in IV therapy (ref. yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e3.746\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e42.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e9.716\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e184.704\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e3.825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.751\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e45.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e10.512\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e199.794\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"13\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIV training programs (ref. yes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e2.363\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e10.621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e4.916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e22.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.323\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e5.548\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e2.944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e10.459\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: CI, confidence interval; OR, odds-ratio.\u003c/p\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eTo our knowledge, this is the first study to explore clusters of nurses’ core competency in IV therapy. This study used LPA to reveal significant heterogeneity in clinical nurses of IV therapy core competency, identifying three categories: ‘High IV Competence’, ‘Moderate IV Competence’ and ‘Low IV Competence’. In this study, nearly half of nurses in the moderate group (45.9%) and over two-fifths in the low group (41.3%), while only 12.8% achieved high competency, which highlights a critical need for targeted improvement. Notably, all three profiles showed consistent relative performance across the five competency dimensions: professional development scored highest (mean=2.20), while professional attitude scored lowest (mean=1.48), with theoretical knowledge, critical thinking, and IV therapy skills in between. This dimension-specific variability offers insights into how competency is prioritized in nursing practice. The strength in professional development reflects clinical teaching, and research innovation abilities which may be because IV therapy core competency represents a critical determinant of IV therapy quality and the specialized skills needed for effective intravenous treatments[18]. As IV technology advances, clinical nurses need not only practical skills but also stronger learning, teaching, and research innovation abilities for professional development. Modern nursing education frameworks increasingly prioritize lifelong learning, requiring nurses to engage in ongoing professional development to maintain licensure and adapt to evolving clinical guidelines[19]. Many healthcare institutions now mandate or incentivize participation in workshops, certifications, and teaching activities related to IV therapy (e.g., training new staff), which directly strengthens skills in clinical teaching and reflective practice. In contrast, the weakness in professional attitude encompassing patient communication, empathy, or safety mindfulness raises concerns, as attitude directly impacts patient satisfaction and adherence to care protocols. Possible drivers include time constraints from high workloads, which prioritize technical efficiency over interpersonal care, or curricula that overemphasize technical skills at the expense of attitude. Nurses in the ‘High-IV’ group excel not only in technical skills but also in attitude and critical thinking, indicating that competency is shaped by systemic factors rather than isolated skill deficits[20], underlying enablers (e.g., access to training, mentorship, or organizational support) may foster holistic proficiency.\u003c/p\u003e\n\u003cp\u003eThe lack of specialist certification in IV therapy and non-participation in IV training programs were strongly and significantly associated with lower competency levels (low or moderate vs. high). In contrast, demographic variables (age, education) and professional factors (work experience, hospital level) showed no significant associations with IV core competency. These findings are consistent with previous research emphasizing the role of specialized training in enhancing clinical skills, which found that targeted training programs improve proficiency in IV catheter insertion and complication management[21, 22]. Our results further reinforce that formal training programs beyond general professional experience are critical for developing high-level IV competency. Notably, the lack of association between work experience and competency contrasts with a few earlier studies [23, 24], which may reflect differences in how 'experience' was operationalized (e.g., years in practice vs. hours of IV-specific practice). The strong association between specialist certification/training and higher competency likely reflects the structured, skill-specific content of these programs, which focus on evidence-based practices, advanced techniques, and error prevention areas critical for IV therapy safety and effectiveness. The non-significant associations with age, education, or work experience suggest that competency in IV therapy is not merely a function of general professional maturity but requires targeted skill development. This may explain why even experienced providers without specialized training showed no advantage in competency levels[25]. Practically, these findings underscore the need for healthcare institutions to prioritize IV therapy training programs and incentivize specialist certification. Standardizing access to such training could help reduce variability in competency and improve patient outcomes, as low IV competency is linked to higher rates of infiltration, infection, and patient discomfort[26]. Theoretically, our results support the construct of 'competency as skill-specific' rather than a byproduct of general professional development, challenging assumptions that experience alone drives clinical proficiency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1 Strength and Limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has several strengths. First, the use of LPA allowed for the identification of naturally occurring competency subgroups, offering a more nuanced understanding than traditional aggregate scoring methods. Second, the large sample size (n=821) enhances the generalizability of the latent profiles and regression findings. Third, the multivariate logistic regression adjusted for multiple potential confounders, strengthening causal inference regarding the role of training and certification.\u003c/p\u003e\n\u003cp\u003eMeanwhile, several limitations should be acknowledged. First, the cross-sectional design precludes conclusions about causality; for example, while training participation correlates with higher competency, we cannot definitively conclude that training causes improved performance (reverse causality, e.g., more competent nurses may seek out training, cannot be ruled out). Second, competency was assessed via self-reported questionnaires, which may be subject to response bias. Future studies could incorporate objective skill assessments to validate self-reported scores. Third, unmeasured variables such as institutional support for training, mentorship availability, or workload stress may also influence competency and were not included in the regression model. Finally, the sample was drawn from 20 provincial regions, while geographic distribution disparities existed (Guangdong 87.2%).\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eThis study uses LPA to identify three distinct IV therapy competency profiles among nurses, in which only 12.8% achieved high competency. This reminds us of a critical need for IV therapy core competency improvement in clinical nurses. Furthermore, we find specialized certification and continuous training are pivotal to enhancing nurses’ IV therapy core competency, while traditional demographic and professional factors play a limited role, which underscore the urgency of targeted interventions to address IV therapy competency gaps, the need to prioritize specialist nurses’ development and mandatory continuous training in IV therapy. Firstly, hospitals should establish structured certification programs for IV specialists, ensuring they receive advanced training in complex procedures (e.g., central line insertion, managing difficult venous access) and serve as mentors for general nurses. Secondly, competency assessment should focus on skill-based evaluations rather than proxy measures like tenure or degree. Additionally, standardized, evidence-based training in IV therapy are essential. With consistent access to this training, even nurses in secondary hospitals or those with limited experience can achieve high competency. Nursing managers should conduct regular competency audits that include simulation-based assessments of intravenous techniques and complication management, enabling precise identification of gaps and targeted interventions to enhance the quality of IV therapy and patient safety.\u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eIV: Intravenous.\u003c/p\u003e\n\u003cp\u003eLPA: Latent profile analysis.\u003c/p\u003e\n\u003cp\u003eVADs: Venous access devices.\u003c/p\u003e\n\u003cp\u003eAIC: Akaike information criterion.\u003c/p\u003e\n\u003cp\u003eBIC: Bayesian information criterion.\u003c/p\u003e\n\u003cp\u003eaBIC: adjusted Bayesian information criterion.\u003c/p\u003e\n\u003cp\u003eLMR: Lo-Mendell-Rubin.\u003c/p\u003e\n\u003cp\u003eBLRT: Bootstrapped likelihood ratio test.\u003c/p\u003e\n\u003cp\u003eCI: Confidence interval.\u003c/p\u003e\n\u003cp\u003eOR: Odds-ratio.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was reviewed and approved by the Research Ethics Committee of the Second Affiliated Hospital of Guangzhou University of Chinese Medicine (approval no. BE2020-045-01). The study protocol conformed to the Declaration of Helsinki, with voluntary participation and electronic informed consent obtained prior to survey access.The initial page of the questionnaire, provided comprehensive information on the study’s aims, procedures, and ethical safeguards. Participants were assured that their data would remain confidential and anonymous.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting the findings of this study are available on request from the corresponding author. The data is not publicly available due to privacy or ethical restrictions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was conducted with the support of Guangdong Nurses Association (NO. P2023035).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy conception and design: LS, QHH, JTS; Data collection: DYH, QQY, LY, ZJZ; Data analysis and interpretation: LS, ZJZ, LY; Drafting of the article: LS, YL. Critical review of the manuscript: QHH, XW. All the authors have carefully reviewed the article and approved the final draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to all hospital administrators and nurses who took part in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOza-Gajera BP, Davis JA, Farrington C, Lerma EV, Moossavi S, Sheta MA, Dwyer A, Almehmi A: \u003cstrong\u003ePICC line management among patients with chronic kidney disease\u003c/strong\u003e. \u003cem\u003eThe journal of vascular access \u003c/em\u003e2023, \u003cstrong\u003e24\u003c/strong\u003e(2):329-337.\u003c/li\u003e\n\u003cli\u003ePittiruti M, Hamilton H, Biffi R, MacFie J, Pertkiewicz M: \u003cstrong\u003eESPEN Guidelines on Parenteral Nutrition: central venous catheters (access, care, diagnosis and therapy of complications)\u003c/strong\u003e. \u003cem\u003eClinical nutrition (Edinburgh, Scotland) \u003c/em\u003e2009, \u003cstrong\u003e28\u003c/strong\u003e(4):365-377.\u003c/li\u003e\n\u003cli\u003eDuwadi S, Zhao Q, Budal BS: \u003cstrong\u003ePeripherally inserted central catheters in critically ill patients - complications and its prevention: A review\u003c/strong\u003e. \u003cem\u003eInternational journal of nursing sciences \u003c/em\u003e2019, \u003cstrong\u003e6\u003c/strong\u003e(1):99-105.\u003c/li\u003e\n\u003cli\u003eBerger S, Winchester K, Principe RB, Culverwell E: \u003cstrong\u003ePrevalence of peripheral intravenous catheters and policy adherence: A point prevalence in a tertiary care university hospital\u003c/strong\u003e. \u003cem\u003eJournal of clinical nursing \u003c/em\u003e2022, \u003cstrong\u003e31\u003c/strong\u003e(15-16):2324-2330.\u003c/li\u003e\n\u003cli\u003eEstrada-Orozco K, Cantor-Cruz F, Larrotta-Castillo D, D\u0026iacute;az-R\u0026iacute;os S, Ruiz-Cardozo MA: \u003cstrong\u003eCentral venous catheter insertion and maintenance: Evidence-based clinical recommendations\u003c/strong\u003e. \u003cem\u003eRevista colombiana de obstetricia y ginecologia \u003c/em\u003e2020, \u003cstrong\u003e71\u003c/strong\u003e(2):115-162.\u003c/li\u003e\n\u003cli\u003eBell JA, Spencer TR: \u003cstrong\u003eImplementing an emergency department vascular access team: A quality review of training, competency, and outcomes\u003c/strong\u003e. \u003cem\u003eThe journal of vascular access \u003c/em\u003e2021, \u003cstrong\u003e22\u003c/strong\u003e(1):81-89.\u003c/li\u003e\n\u003cli\u003eQuinn M, Horowitz JK, Krein SL, Gaston A, Ullman A, Chopra V: \u003cstrong\u003eThe role of hospital-based vascular access teams and implications for patient safety: A multi-methods study\u003c/strong\u003e. \u003cem\u003eJournal of hospital medicine \u003c/em\u003e2024, \u003cstrong\u003e19\u003c/strong\u003e(1):13-23.\u003c/li\u003e\n\u003cli\u003eWoody G, Davis BA: \u003cstrong\u003eIncreasing nurse competence in peripheral intravenous therapy\u003c/strong\u003e. \u003cem\u003eJournal of infusion nursing : the official publication of the Infusion Nurses Society \u003c/em\u003e2013, \u003cstrong\u003e36\u003c/strong\u003e(6):413-419.\u003c/li\u003e\n\u003cli\u003eQuadros AI, Stocco JGD, Cristoff C, Alcantara CB, Pimenta AM, Machado BGS: \u003cstrong\u003eAdherence to central venous catheter maintenance bundle in an intensive care unit\u003c/strong\u003e. \u003cem\u003eRevista da Escola de Enfermagem da U S P \u003c/em\u003e2022, \u003cstrong\u003e56\u003c/strong\u003e:e20220077.\u003c/li\u003e\n\u003cli\u003eMeszaros MJ, de Almeida AO, Aoki RN, Vieira APG, Castelani MA, Silva JLG, Lima MHM, Oliveira-Kumakura ARS: \u003cstrong\u003eDevelopment and Testing of an Objective Structured Clinical Examination for Evaluating Nurses in Infusion Therapy\u003c/strong\u003e. \u003cem\u003eJournal of infusion nursing : the official publication of the Infusion Nurses Society \u003c/em\u003e2025, \u003cstrong\u003e48\u003c/strong\u003e(1):36-43.\u003c/li\u003e\n\u003cli\u003eHackett A, Wells C, Zhang Z, Kero J, Soriano J, Rivera J, Brito A, Guiney J, Leibner E, Kohli-Seth R: \u003cstrong\u003eDevelopment of a Peripheral Intravenous Access Training Program for Nurses in the Pediatric Intensive Care Units\u003c/strong\u003e. \u003cem\u003eJournal of pediatric nursing \u003c/em\u003e2021, \u003cstrong\u003e61\u003c/strong\u003e:394-403.\u003c/li\u003e\n\u003cli\u003ede Souza LC, Campos JF, de Oliveira HC, de Azevedo Vianna C, de Bakker GB, Machado DM, Brand\u0026atilde;o MAG, da Silva RC: \u003cstrong\u003eEffect of rapid cycle deliberate practice in peripheral intravenous catheters insertion training: A simulation experimental study\u003c/strong\u003e. \u003cem\u003eNurse education in practice \u003c/em\u003e2023, \u003cstrong\u003e71\u003c/strong\u003e:103734.\u003c/li\u003e\n\u003cli\u003eUzelli Yilmaz D, Sari D: \u003cstrong\u003eExamining the effect of simulation-based learning on intravenous therapy administration\u0026apos; 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intravenous catheter management knowledge and confidence: A cross-sectional study\u003c/strong\u003e. \u003cem\u003eNurse education in practice \u003c/em\u003e2023, \u003cstrong\u003e73\u003c/strong\u003e:103816.\u003c/li\u003e\n\u003cli\u003eYilmaz DU, Yilmaz D, Karaman D: \u003cstrong\u003eClinical nurses\u0026apos; knowledge and practices on routine care related to the prevention of complications of peripheral intravenous therapy: A cross-sectional study\u003c/strong\u003e. \u003cem\u003eThe journal of vascular access \u003c/em\u003e2023, \u003cstrong\u003e24\u003c/strong\u003e(2):277-283.\u003c/li\u003e\n\u003cli\u003eHulse AL: \u003cstrong\u003eClinical competency assessment in intravenous therapy and vascular access: part 1\u003c/strong\u003e. \u003cem\u003eBritish journal of nursing (Mark Allen Publishing) \u003c/em\u003e2013, \u003cstrong\u003e22\u003c/strong\u003e(16):933-934, 936-937.\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, Intravenous therapyNurses, Intravenous therapy, Core competence, Latent profile analysis, Risk factorsCore competence, Latent profile analysis, Risk factors","lastPublishedDoi":"10.21203/rs.3.rs-7251559/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7251559/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground \u003c/strong\u003eNurses’ core competency in intravenous(IV) therapy directly impacts patient safety and treatment outcomes. This study aimed to identify latent classes of nurses’ intravenous therapy core competency using latent profile analysis (LPA) and explore key factors influencing these classes to inform targeted interventions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eA multicenter cross-sectional study was conducted from October 2023 to January 2024, involving 821 clinical nurses from 20 provincial-level regions in China. Data was collected using the validated Core Competency in Intravenous Therapy Scale. LPA was used to identify latent competency classes, and multivariate logistic regression was performed to explore risk factors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e Three distinct latent classes were identified: (1) ‘Low-IV Core Competence’ (41.3%), with low scores across all dimensions; (2) ‘Moderate-IV Core Competence’ (45.9%), with medium scores across all dimensions; and (3) ‘High-IV Core Competence’ (12.8%), with high scores across all dimensions. Multivariate logistic regression showed that non-specialist nurses in intravenous therapy (Low vs. High: OR=42.362, p\u0026lt;0.001; Moderate vs. High: OR=45.829, p\u0026lt;0.001) and non-participation in intravenous therapy training programs (Low vs. High: OR=10.621, p\u0026lt;0.001; Moderate vs. High: OR=5.548, p\u0026lt;0.001) were strongly associated with lower competency. No significant associations were found with age, education level, hospital level, or work experience.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e This study reveals a critical need for IV therapy core competency improvement in clinical nurses and underscore the importance of investments in IV specialist nurse development and standardized training to improve IV therapy quality and patient safety.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration \u003c/strong\u003eNot Applicable.\u003c/p\u003e","manuscriptTitle":"Latent Profile Analysis of Core Competency in Intravenous Therapy Among Chinese Clinical Nurses: A Multicenter Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 05:11:53","doi":"10.21203/rs.3.rs-7251559/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-19T09:47:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-18T09:43:20+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-12T12:10:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80981693007754566363638293788771374851","date":"2025-09-02T12:39:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259046807110125524254973906999729876844","date":"2025-08-25T08:20:38+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-25T07:43:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-25T07:38:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-08-12T17:38:49+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-08-07T07:33:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nursing","date":"2025-08-07T07:10:58+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":"590c4b7b-ff6a-4b8f-afe9-8da0febcb8c3","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-10T16:08:49+00:00","versionOfRecord":{"articleIdentity":"rs-7251559","link":"https://doi.org/10.1186/s12912-025-04007-7","journal":{"identity":"bmc-nursing","isVorOnly":false,"title":"BMC Nursing"},"publishedOn":"2025-11-05 15:57:44","publishedOnDateReadable":"November 5th, 2025"},"versionCreatedAt":"2025-09-03 05:11:53","video":"","vorDoi":"10.1186/s12912-025-04007-7","vorDoiUrl":"https://doi.org/10.1186/s12912-025-04007-7","workflowStages":[]},"version":"v1","identity":"rs-7251559","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7251559","identity":"rs-7251559","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}