Current status and influencing factors of digital competence among nurses in intensive care units: a cross-sectional study

Current status and influencing factors of digital competence among nurses in intensive care units: a cross-sectional study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Current status and influencing factors of digital competence among nurses in intensive care units: a cross-sectional study Zhengang Wei, Congcong Liu, Jicheng Zhang, Chunmei Fan, Zhenfeng Zhou, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7851326/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Digital competence builds upon information literacy, extending and expanding it in the digital age. The ICU is characterized by complex, data-intensive environments and high clinical workload, making it a critical setting for the application of information technology. At the same time, the integration of nursing practice with digital tools and technologies is deepening, placing greater demands on ICU nurses' digital competence. Objective To investigate the digital competence of ICU nurses and analyze the relevant influencing factors, providing valuable insights for the development of personalized intervention strategies. Methods This study employed a cross-sectional design. From December 2024 to March 2025, a convenience sampling method was used to survey 576 ICU nurses in Shandong Province. Data were collected using general information questionnaires, the Digital Competence Scale, the Organizational Support Scale, and the Innovation Self-Efficacy Scale. Univariate analysis, Pearson correlation analysis, and multiple linear regression analysis were conducted to explore the factors influencing the digital competence of ICU nurses. Results The total score on the Digital Competence Scale was 48.58 ± 7.02, with an average item score of 4.08 ± 0.73. Innovation self-efficacy (r = 0.472, P < 0.001) and organizational support (r = 0.319, P < 0.001) were significantly positively correlated with digital competence. Multiple linear regression analysis indicated that gender, whether the nurse had received relevant information technology training, innovation self-efficacy, and organizational support were significant factors influencing digital competence among clinical nurses (P < 0.01). Conclusion Although ICU nurses demonstrate a positive attitude toward digital technologies, there remains a significant gap in their practical skills and knowledge application. With the increasing use of digital tools in healthcare, enhancing ICU nurses' digital skills is crucial for improving nursing quality and patient outcomes. Future research should focus on long-term digital competence development programs and explore additional factors influencing the practical application of these skills, further advancing the digital transformation of clinical nursing practice. Digital competence ICU nurses Organizational support Innovative Self-Efficacy Influencing factors Introduction In 2006, the final 'Eight Key Competences' published by the European Parliament and the Council of the European Union recognized digital competence as one of the core skills essential for lifelong learning among the public [ 1 ]. Digital competence is an extension of information literacy, building upon it and adapting it to the digital age [ 2 ]. Although the concepts overlap, they differ in focus. Information literacy primarily emphasizes computer skills, information literacy, and information management [ 3 ]. In contrast, digital competence focuses on the comprehensive ability to effectively use digital technology across various tasks and contexts. It encompasses not only an understanding of technology but also practical skills and the attitude and behaviors exhibited when interacting with technology [ 4 ]. As information technology continues to evolve, clinical nurses now spend a significant portion of their time not only providing direct patient care but also mastering the use of electronic health record systems, and they must also be skilled in managing and protecting patient data and proficiently operating telemedicine devices and software to ensure the delivery of efficient and secure healthcare services [ 5 – 7 ]. The resulting technological pressures have become a common issue in clinical work environments [ 8 ]. Research has shown that sustained technological pressure can lead to nurse burnout, reduced job satisfaction, and even an increased intention to leave the profession [ 9 – 11 ]. Therefore, developing strong digital competence is essential for clinical nurses to fulfill diverse responsibilities in the era of healthcare digital transformation. It supports more effective decision-making, enhances patient safety, and fosters innovation in nursing practice [ 8 ]. The Intensive Care Unit (ICU) is a complex and data-intensive clinical environment, characterized by high clinical workload, making it a critical area for information technology applications [ 12 – 13 ]. Critically ill patients generate vast amounts of data, with monitoring equipment at the bedside, such as blood gas analyzers, ventilators, infusion pumps, continuous blood purification devices, and extracorporeal membrane oxygenation, requiring real-time management [ 14 ]. The frequency and scope of clinical monitoring and sampling for these patients far exceed those of regular patients [ 15 ]. Additionally, as digital technologies evolve rapidly, the integration of digital tools into nursing practice has become increasingly profound, raising the demands on ICU nurses' digital competencies to ensure high-quality and efficient care [ 16 – 17 ]. As a result, there is an urgent need for a reliable tool specifically designed to assess the digital skills of ICU nurses, as previous studies have highlighted that organizational support is a key factor in creating a positive digital experience for healthcare professionals, and furthermore, healthcare workers need intrinsic motivation and a willingness to engage with digital tools; innovative solutions to workplace challenges can encourage them to explore the application of digital technologies in ICU settings, thereby fostering the development of their digital capabilities [ 2 , 18 ]. Furthermore, relevant studies have identified various factors associated with digital competency levels, including innovation behaviors, educational background, and participation in information technology training [ 19 – 21 ]. International research on the digital competencies of healthcare professionals has developed a relatively systematic theoretical framework and practical approaches [ 2 ]. In contrast, studies in China have largely focused on describing the current status of healthcare professionals’ information literacy and skills, with little progress in developing tools to assess digital competencies [ 22 ]. To address this gap, our preliminary work introduced the Digital Competence Questionnaire (DCQ), developed by Swiss scholars such as Golz [ 23 ], into China, where it was translated, culturally adapted, and psychometrically validated. Building on this foundation, the present study applies the DCQ to assess the digital competencies of ICU nurses, analyzes the factors influencing these competencies, and provides evidence to inform the design of information technology training programs and targeted interventions, with the ultimate goal of improving the quality and effectiveness of nursing care in intelligent healthcare environments. Methods Study design This study utilizes a cross-sectional design and employs convenience sampling to select ICU nurses from 5 secondary hospitals and 9 tertiary hospitals in Shandong Province between December 2024 and March 2025. Participant selection and setting This study employs an online cross-sectional survey method to collect electronic questionnaire data, ensuring informed consent is obtained. The inclusion criteria for the study population were as follows: (1) aged ≥ 18 years; (2) holding a valid nursing license; (3) employed in an ICU for over one year; (4) willing to voluntarily participate in the study with informed consent. The exclusion criteria were as follows: (1) nursing interns or advanced training nurses; (2) nurses absent due to leave or external training. The sample size for multi-factor analysis is typically 10 to 20 times the number of independent variables [ 24 ]. In this study, 12 independent variables were considered. After accounting for a 20% invalid response rate, the required sample size ranged from 150 to 300. A larger sample size allows for a more comprehensive consideration of various factors, enhancing the generalizability and representativeness of the results. In total, 596 questionnaires were collected, with 20 invalid responses excluded, resulting in 576 valid responses and an effective response rate of 96.6%. Ethics(SWYX: NO.2025 − 239). All participants provided informed consent and voluntarily agreed to participate. Measures General Information Questionnaire The design was developed by the research team after reviewing relevant literature and conducting internal discussions. The design includes 11 items: gender, age, education level, marital status, professional title, years of work experience, department, position, hospital type, ICU type, and whether the participant has received training in relevant information technology. Digital Competence Questionnaire The Digital Competence Questionnaire (DCQ) was developed by Swiss scholars Golz et al [ 23 ]. in 2023 based on the Digital Competence Framework. Building on 26 initial items derived from a prior Delphi study, the questionnaire was further validated through psychometric testing and finalized with 12 items [ 25 ]. Karvouniari et al [ 26 ]. assessed the reliability and validity of this tool among healthcare personnel in Greece, finding a Cronbach's α of 0.826, which suggests that it is suitable for measuring the digital competence of clinical nurses. Bulut also adapted the DCQ, and the Turkish version has been validated as an effective and reliable tool for assessing nurses' digital competence [ 27 ]. At the outset of this study, our research team completed the cultural adaptation and revision of the Chinese version of the DCQ [ 28 ]. The Chinese version consists of two dimensions: Knowledge and Skills (6 items) and Attitudes (6 items). Each item uses a 5-point Likert scale, ranging from "strongly disagree" to "strongly agree," with scores from 1 to 5. The total score ranges from 12 to 60. Clinical nurses can complete the questionnaire in 3 minutes, and higher scores indicate a higher self-perceived level of digital competence. The overall Cronbach's α value of the questionnaire is 0.970, with Cronbach's α for the individual dimensions ranging from 0.921 to 0.945. The scale's split-half reliability is 0.912, and the test-retest reliability is 0.846. Creative Self-Efficacy The Creative Self-Efficacy Questionnaire was developed by Carmeli and Schaubroeck [ 29 ] in 2007 and subsequently revised and adapted to the Chinese context by Gu Yuandong [ 30 ] and colleagues in 2010. Initially designed for organizational populations, this unidimensional instrument consists of eight items that assess employees’ confidence in their creative abilities, including completing work tasks, achieving goals, and addressing challenges in innovative ways. Each item is scored on a five-point Likert scale (1 = “strongly disagree” to 5 = “strongly agree”), with higher scores reflecting stronger innovative self-efficacy. The original scale demonstrated strong internal reliability, with a Cronbach’s alpha of 0.920. Perecived Organizational Support Scale The Perceived Organizational Support Scale was developed by Chen Zhixia [ 31 ] in 2006 and revised by Zuo Hongmei [ 32 ] and colleagues in 2009, resulting in the Nurse Perceived Organizational Support Scale, which has been widely applied in nursing research. The scale comprises 13 items across two dimensions: emotional support (items 1–10) and instrumental support (items 11–13). Emotional support represents the encouragement and care offered by the organization, whereas instrumental support denotes the provision of tools and resources required for employees to perform their tasks. Each item is rated on a five-point Likert scale (1 = “strongly disagree” to 5 = “strongly agree”), producing a total score between 13 and 65. Higher scores indicate stronger perceived organizational support among nurses. Based on the mean item score, organizational support is categorized into three levels: low (1.00–2.33), moderate (2.34–3.66), and high (3.67–5.00). The scale demonstrates excellent internal consistency, with a Cronbach’s alpha of 0.920. Variable Collection This study used the Wenjuanxing platform to conduct a status survey. After obtaining approval from the relevant management departments, the researchers shared the Wenjuanxing link, study purpose, and filling instructions in WeChat and DingTalk groups of ICU departments in various hospitals. ICU nurses anonymously and voluntarily completed the survey. A standardized set of instructions and filling guidelines was provided at the beginning of the questionnaire. To ensure data quality and completeness, submission standards were set on the Wenjuanxing platform, allowing each IP address to submit only one response and requiring all questions to be answered before submission. After data collection, two researchers reviewed the responses to ensure reliability, excluding invalid questionnaires. Questionnaires with excessively short completion times, severe logical inconsistencies, or patterns of answers (e.g., more than 50% of questions answered identically) were discarded. Statistical analysis Data were entered and analyzed using Excel 2019 and IBM SPSS version 29.0(IBM Inc, Armonk, NY, USA). Categorical variables were summarized using frequencies and percentages, while continuous variables conforming to a normal distribution were described as mean ± standard deviation. Comparisons between groups were conducted using independent-samples t tests and one-way analysis of variance (ANOVA). Pearson correlation analysis was employed to examine the relationships among nurses’ digital competence, innovative self-efficacy, and perceived organizational support. Variables identified as statistically significant in univariate analyses were subsequently included as independent variables in multiple stepwise linear regression models to explore factors influencing digital competence among ICU nurses. Statistical significance was defined as a P value of less than .05. Results General information and digital competence of ICU nurses The results of the univariate analysis in this study indicate that age, education level, hospital tier, and whether nurses have received relevant information technology training are significant factors influencing clinical nurses' digital competence, with statistically significant differences (P < 0.05). These findings are detailed in Table 1 . The total score of the digital competence scale for 576 ICU nurses was 48.58 ± 7.02, with an average item score of 4.08 ± 0.73. The attitude dimension scored 24.50 ± 3.69, with an average item score of 4.11 ± 0.75. The knowledge and skills dimension scored 24.09 ± 3.67, with an average item score of 4.05 ± 0.71. In the attitude dimension, the top three items with the highest average scores were Item 4, Item 2, and Item 6. In the Knowledge & Skills dimension, the top three items with the highest average scores were Item 10, Item 12, and Item 11, as shown in Table 2 . Table 1 Univariate Analysis of Demographics and Digital Competence of ICU Nurses (n = 576) Items n(%) Digital Competence Score(x ± s) t/F P Gender -1.213 0.225 Male 126(21.88) 49.25 ± 8.28 Female 450(78.12) 48.40 ± 6.63 Age(years) 3.149 0.025 45 10(1.74) 45.00 ± 11.98 Marital status 1.325 0.266 Married 355(61.63) 48.42 ± 7.25 Unmarried 214(37.15) 48.97 ± 6.69 Widowed/divorced 7(1.22) 45.00 ± 3.79 Educational level 4.557 <0.001 Secondary and tertiary education 37(6.42) 47.38 ± 10.42 Undergraduate 486(84.38) 48.53 ± 6.86 Graduate and above 53(9.20) 49.94 ± 5.26 Professional Title 0.411 0.663 Primary level 321(55.72) 48.64 ± 7.01 Intermediate level 234(40.63) 48.40 ± 7.13 Advanced level 21(3.65) 49.81 ± 6.22 Years of work (years) 0.581 0.559 1–5 240(41.67) 48.92 ± 6.67 6–10 202(35.07) 48.56 ± 6.84 >10 134(23.26) 48.20 ± 7.54 Job Position 1.754 0.154 Clinical Nurse 389(67.53) 48.64 ± 6.92 Nursing administrator 89(15.45) 48.07 ± 6.96 Nursing Team Leader 52(9.03) 50.46 ± 5.94 Others 46(7.99) 47.40 ± 8.46 Hospital level (tier) 5.883 <0.001 Tertiary 519(90.10) 48.71 ± 6.94 Secondary 57(9.90) 48.06 ± 6.58 ICU type 0.382 0.820 Specialized ICU 153(26.56) 48.90 ± 5.72 Comprehensive ICU Received relevant information training 423(73.44) 47.66 ± 5.88 6.102 <0.001 Yes 370(64.24) 49.88 ± 6.90 No 206(35.76) 46.26 ± 6.65 Table 2 Ranking of digital competency scores of ICU nurses(N = 576) Items related to digital competency Rank Score Total 4.08 ± 0.73 Attitude 4.11 ± 0.75 4.I believe that digital technology provides numerous benefits in terms of quality of care. 1 4.17 ± 0.82 2.I enjoy using digital technology at my workplace. 2 4.10 ± 0.71 6.I believe that digital technology is beneficial for my patients. 3 4.09 ± 0.72 3.I like to use digital technology at work. 4 4.08 ± 0.72 5.I believe that digital technology improves patient outcomes. 5 4.05 ± 0.75 1.Digital technology fits well with the way I like to work. 6 4.01 ± 0.79 Knowledge & Skills 4.05 ± 0.71 10.I feel confident about using digital technology to obtain data and information on clinical care. 1 4.25 ± 0.67 12.I feel confident in dealing with confidentiality issues relating to digital technology at my workplace. 2 4.13 ± 0.68 11.I am able to reach conclusions based on information acquired through digital technologies. 3 4.10 ± 0.69 9.I feel confident about using digital technology to communicate. 4 4.05 ± 0.70 8.I feel confident about using digital technology to find relevant information. 5 4.01 ± 0.72 7.I am familiar with the digital technologies at my workplace. 6 3.95 ± 0.75 Analysis of ICU nurses' digital competence and its relationship with innovation self-efficacy and organizational support A total of 576 ICU nurses were surveyed to analyze their digital competence and its relationship with innovation self-efficacy and organizational support. The average scores for innovation self-efficacy and organizational support were 30.75 ± 6.25 and 54.54 ± 7.07, respectively. The emotional support dimension scored 41.28 ± 6.17, while the instrumental support dimension scored 8.91 ± 0.80. The analysis confirmed that the innovation self-efficacy, organizational support, and their respective dimensions of the nurses all passed normality tests. Pearson correlation analysis indicated that digital competence was positively correlated with innovation self-efficacy (r = 0.472, P < 0.001) and organizational support (r = 0.319, P < 0.001). Furthermore, positive correlations were observed between digital competence and both the emotional and instrumental support dimensions (P < 0.001). Refer to Table 3 . Table 3 Correlational Analysis of ICU Nurses' Digital Competency, Innovative Self-Efficacy, and Perceived Organizational Support (N = 576) Items Score(x ± s) r P value Creative Self-Efficacy 30.75 ± 6.25 0.472 < 0.001 Perecived Organizational Support 54.54 ± 7.07 0.319 < 0.001 Notes r: Correlation Coefficients with ICU Nurses' Digital Competency Multiple linear regression analysis of ICU nurses' digital competence The total score of ICU nurses' digital competence was set as the dependent variable, while variables with p < 0.05 in univariate analysis, along with organizational support and innovation self-efficacy, were selected as independent variables for stepwise regression. The inclusion criteria were p 0.05. The assignment method for the independent variables is shown in Table 4 , with the raw scores of the innovation self-efficacy and organizational support scales directly used. The analysis revealed that education level, hospital tier, years of service ≥ 6, organizational support, and innovation self-efficacy were positive predictors of digital competence, as shown in Table 5 . Table 4 Assignment methods of independent variables Notation Variable Allocation method X1 Age(years) 45 = 4 X2 Educational level Secondary and tertiary education = 1; Undergraduate = 2; Graduate and above = 3 X3 Hospital level (tier) Tertiary = 1; Secondary = 2 X4 Received relevant information training Yes = 1; No = 2 Table 5 Multiple linear regression analysis of the factors influencing ICU nurses' digital competence (n = 576) Variable B Value Standard error β t value P value VIF Constant 28.717 2.899 2.408 9.906 < 0.001 Educational level Hospital level (tier) 0.089 0.122 1.301 1.118 0.033 0.082 1.974 3.017 0.049 0.003 1.014 1.023 Received relevant information training 0.368 0.597 0.123 5.891 < 0.001 1.018 Creative Self-Efficacy 0.546 0.041 0.050 8.417 < 0.001 1.007 Perecived Organizational Support 0.150 0.036 0.014 4.142 < 0.001 1.019 Notes F = 45.142, P < 0.001, R 2 = 0.284, adjusted R 2 = 0.277. VIF: Variance inflation factor Discussion Overall digital competence of ICU nurses was above average The results of this study indicate that the total score for digital competence among 576 ICU nurses was 48.58 ± 7.02, with an average item score of 4.08 ± 0.73, reflecting a moderately high level of digital competence. These findings are consistent with those of Karvouniari et al., 26 who conducted a cross-sectional study on 494 healthcare professionals. However, with the rapid development of artificial intelligence (AI) technologies in the healthcare field, such as intelligent diagnostics, telemedicine, and personalized treatment recommendations, the demands on nurses' digital competence are increasing. The role of nurses is expected to evolve from mere executors of tasks to bridges between technology and humanistic care. Nurses will not only need to possess fundamental medical and nursing skills but also be proficient with new technological tools to ensure they can play a crucial role in highly digitized healthcare environments. Therefore, ICU nurses' digital competence, particularly in the application of AI technologies, will directly influence the quality of healthcare services and patient treatment outcomes. In the two dimensions investigated in this study, the attitude dimension scored higher, while the knowledge and skills dimension scored lower. This suggests that ICU nurses generally possess a positive attitude and confidence regarding digital competence but still face challenges in mastering the knowledge and skills necessary for the practical application of digital technologies. Konttila et al [ 2 ], also highlighted that the digital competence of healthcare professionals is closely related to clinical knowledge and skills, and digital competence should be seen as an integral part of everyday activities. This phenomenon may reflect the fact that while ICU nurses acknowledge and accept the importance of digital technologies, they encounter difficulties and limitations in acquiring practical operational skills and applying them effectively in their work. ICU nurses with a stronger sense of organizational support demonstrate higher levels of digital competence Multiple linear regression analysis showed that organizational support significantly influences the digital competence of ICU nurses ( p < 0.001). A positive correlation was also found between perceived organizational support and digital competence (r = 0.319, p < 0.001). Organizational support acts as a catalyst for developing digital competence by integrating managerial support, adequate resources, and a culture that values technological innovation [ 2 ]. Supportive leadership enhances nurses’ motivation to acquire digital skills by clarifying the practical value of technologies (e.g., electronic health records, wireless monitoring systems) and reducing operational barriers [ 2 ]. When institutions allocate time for training and encourage feedback on system usability, nurses’ confidence in digital platforms improves, even in the high-risk and time-sensitive ICU environment. Adequate resources, including reliable infrastructure, continuous educational programs, and technical support, further provide the foundation for competence development. Conversely, limited equipment access or fragmented training (e.g., one-time workshops without follow-up) can cause frustration and reduce tool utilization [ 33 – 34 ]. In addition, a collaborative organizational culture characterized by knowledge sharing and recognition of digital proficiency sustains competence over time, and mentoring by experienced nurses and acknowledgment of successful technology-driven interventions strengthen the overall digital competence of ICU teams [ 35 ]. This finding aligns with research showing that a positive team climate—marked by support for innovation and participative safety—correlates with healthcare professionals’ motivation to adopt digital technologies [ 36 ]. In the ICU, such a culture is especially critical, as it ensures the rapid and accurate use of digital data in life-saving decisions. In summary, the synergy of leadership, resources, and culture enables organizational support to act as a “multiplier” of nurses’ digital competence, transforming technical access into practical skills and ensuring that digital tools effectively serve both patient care and professional development. ICU nurses with higher levels of innovative self-efficacy generally demonstrate greater digital competence Innovative self-efficacy, a psychological factor, significantly affects the digital competence of ICU nurses ( p < 0.001). It refers to an individual's confidence in overcoming challenges and successfully applying new technologies or methods independently [ 37 ]. In our study, ICU nurses' innovative self-efficacy is strongly associated with their digital skills performance (r = 0.472, p < 0.001). Nurses with higher innovative self-efficacy are more likely to actively adopt and master emerging digital tools and technologies, such as electronic health records and patient monitoring devices [ 38 ]. Additionally, they typically exhibit strong learning abilities and adaptability to new technologies, making them more proactive and effective in using and learning digital tools, and they proactively adopt and apply new nursing techniques while adapting flexibly to challenges in practice, thereby improving both work efficiency and patient care quality [ 39 – 40 ]. This self-efficacy likely arises from nurses' understanding of new technologies, their learning attitudes, and accumulated hands-on experience. When nurses believe in their ability to effectively use new technologies, their digital competence improves as well. Therefore, cultivating and enhancing ICU nurses' innovative self-efficacy not only increases their acceptance of digital technologies but also improves their practical application skills, driving the digital transformation of ICU nursing services. Enhanced Information Technology Training Improves ICU Nurses' Digital Competence This study demonstrated that ICU nurses with information technology training achieved significantly higher scores in overall digital competence and all its dimensions than their untrained counterparts. Consistent with prior research [ 41 – 42 ], these findings underscore the critical role of structured, systematic training in narrowing the digital gap among healthcare providers and offer empirical support for hospitals and nursing education institutions in developing training protocols. A systematic review [ 18 ] further confirmed that multi-modal interventions in digital competency training for nurses and other healthcare providers significantly enhance digital proficiency. Regular training and simulation exercises, for instance, improve nurses' ability to apply information technologies in clinical practice—including electronic health record systems, telemedicine platforms, and patient management software. As the healthcare sector grows increasingly dependent on information technology, nurses' digital competency will become a pivotal factor in enhancing healthcare service quality. Consequently, hospital and nursing administrators should recognize digital competency training as a long-term strategic investment rather than a short-term obligation. Training strategy development should extend beyond basic operational proficiency to focus on establishing a hierarchical, multi-dimensional, and sustainable progressive training framework [ 43 – 44 ]. Additionally, establishing standardized technical support and feedback mechanisms, conducting regular evaluations of training efficacy, and updating training content based on clinical demands and technological progress are critical to sustaining the development of ICU nurses' digital competency and their capacity to address future technological challenges effectively.​ Educational background and hospital level are other factors influencing ICU nurses' digital competence Our analysis indicates that educational background significantly impacts ICU nurses' digital competence ( p = 0.049). ICU nurses with a bachelor's degree or higher demonstrate significantly higher digital competence than those with a diploma, consistent with the findings of Kleib et al [ 45 ]. Nurses with higher education are more likely to have received training in literature and information retrieval, leading to more comprehensive learning and development. However, the small number of graduate-degree nurses in this study may limit the generalizability of our findings. Additionally, ICU nurses with higher education levels tend to have stronger intrinsic motivation to learn and adapt to new technologies, and they are more likely to actively master digital tools to support clinical decision-making and nursing practices, demonstrating higher digital competence [ 46 ]. Therefore, hospital administrators should prioritize continuing education and career development for nursing staff by designing tiered, targeted programs to improve digital competence for ICU nurses with varying educational backgrounds. For example, diploma nurses could receive basic information technology training, while nurses with a bachelor's degree or higher should focus on data analysis and advanced information systems applications, advancing the implementation of nursing informatization. ICU nurses in tertiary hospitals (48.71 ± 6.94) score higher in digital competence than those in secondary hospitals (48.06 ± 6.58). Higher-level hospitals set higher competency expectations for ICU nurses and focus more on enhancing their skills during advanced stages of professional development. Enhancing digital competence helps ICU nurses maintain a continuous learning drive throughout their careers [ 47 ]. Moreover, tertiary hospitals often introduce digital systems, such as electronic health records, clinical decision support systems, and remote monitoring facilities, earlier. Nurses in these hospitals frequently interact with these systems in their daily work, continuously reinforcing and enhancing their digital application skills [ 48 ]. Therefore, it is recommended that secondary and lower-level healthcare institutions increase investments in IT infrastructure, optimize digital training resources, and establish learning exchange mechanisms with higher-level hospitals. This will help reduce the digital competence gap between ICU nurses in different hospitals and enhance the overall information literacy of the nursing workforce. Limitations This study has several limitations that should be acknowledged. First, as a cross-sectional study, it can only demonstrate associations rather than causal relationships between ICU nurses’ digital competence and its influencing factors, such as organizational support and innovative self-efficacy. Second, the use of a convenience sampling method in a single province (Shandong) may limit the generalizability of the findings to other regions or healthcare systems with different technological infrastructures or training practices. Third, the data were collected through self-reported questionnaires, which may be subject to recall bias and social desirability effects, potentially leading participants to overestimate their digital competence. Additionally, although validated measurement tools were employed, unmeasured confounding variables—such as workload intensity, institutional digital maturity, and prior exposure to digital health systems—might also have influenced the results. Future studies should adopt longitudinal or mixed-method designs, expand sampling across multiple provinces or countries, and incorporate objective assessments of digital competence to further validate and refine these findings. Conclusions This study revealed the current state of digital competence among ICU nurses and analyzed its influencing factors. The results indicate that innovation self-efficacy, organizational support, as well as factors such as nurses' educational background and hospital tier, are positively correlated with digital competence. Specifically, higher levels of innovation self-efficacy and stronger organizational support significantly enhance ICU nurses' digital competence. These findings provide a solid foundation for developing targeted digital competence training and intervention strategies. Future research should further explore how to optimize training models and improve nurses' ability to use digital tools effectively in high-pressure environments, thus promoting the digital transformation of ICU nursing practice. Additionally, cross-regional and longitudinal studies will help validate the generalizability of these findings and provide deeper insights into the development of digital health services. Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee of the Affiliated Provincial Hospital of Shandong First Medical University (Approval Number: SWYX: NO.2025 − 239) and was conducted in accordance with the Helsinki Declaration. All participants provided written informed consent and were thoroughly briefed on the study's objectives, as well as the confidentiality and anonymity of their personal information. Additionally, they were assured that their participation was entirely voluntary and that they could withdraw from the study at any stage without consequence. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Funding This work was supported by the National Natural Science Foundation of China (NSFC) (grant number: 61861047); and the Nursing Research Project of Shandong Provincial Hospital (grant number: HL2025-32); Technology Project the China International Medical Foundation (grant number: 2-2018-35-2004). Author Contribution ZW designed the study, collected and analyzed data, interpreted results, and drafted the manuscript. CL and JZ revised the manuscript. XW analyzed data and contributed to the manuscript. CF, ZZ, YS, and MJ assisted in data collection. All authors read and approved the final manuscript. Acknowledgements We would like to express our sincere gratitude to Professor Christoph Golz for providing the original version of the questionnaire during the early stages of the Chinese adaptation process. His support was invaluable throughout the adaptation and subsequent research stages. Additionally, we would like to thank all the participants who contributed to this study. Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. References Council of the European Union. Recommendation of the European Parliament andof the Council of 18 December 2006 on key competences for lifelong learning. https://op.europa.eu/s/oMzI , 2006-12–8. Konttila J, Siira H, Kyngäs H, et al. Healthcare professionals' competence in digitalisation: A systematic review. J Clin Nurs. 2019;28(5–6):745–61. 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Chinese knowledge-worker's perceived organizational support and its related factors. Beijing: China Economic Publishing house; 2006. Zuo HM, Yang H. A study on relationship between organiza tional support emotion and organizational commitment of nurses. Chin Nurs Res. 2009;23(15):1341–3. Zuzelo PR, Gettis C, Hansell AW, et al. Describing the influence of technologies on registered nurses' work. Clin Nurse Spec. 2008;22(3):132–42. Anttila M, Koivunen M, Välimäki M. Information technology-based standardized patient education in psychiatric inpatient care. J Adv Nurs. 2008;64(2):147–56. Rippen HE, Pan EC, Russell C, et al. Organizational framework for health information technology. Int J Med Inf. 2013;82(4):e1–13. Koivunen M, Anttila M, Kuosmanen L, et al. Team climate and attitudes toward information and communication technology among nurses on acute psychiatric wards. Inf Health Soc Care. 2015;40(1):79–90. Tierney P, Farmer S. Creative Self-efficacy: Its Potential An tecedents and Relationship to Creative Performance. Acad Manage Rev. 2002;45(6):1137–48. Xiang D, Ge S, Zhang Z, et al. Relationship among clinical practice environment, creative self-efficacy, achievement motivation, and innovative behavior in nursing students: A cross-sectional study. Nurse Educ Today. 2023;120:105656. El-Sayed BKM, El-Sayed AAI, Alsenany SA, et al. The role of artificial intelligence literacy and innovation mindset in shaping nursing students' career and talent self-efficacy. Nurse Educ Pract. 2025;82:104208. Alshammari MH, Alenezi A. Nursing workforce competencies and job satisfaction: the role of technology integration, self-efficacy, social support, and prior experience. BMC Nurs. 2023;22(1):308. Dimitri P, Fernandez-Luque L, Koledova E, et al. Accelerating digital health literacy for the treatment of growth disorders: The impact of a massive open online course. Front Public Health. 2023;11:1043584. Ferreira JC, Elvas LB, Correia R, Mascarenhas M. Empowering Health Professionals with Digital Skills to Improve Patient Care and Daily Workflows. Healthc (Basel). 2025;13(3):329. Mills J, Francis K, McLeod M, et al. Enhancing computer literacy and information retrieval skills: A rural and remote nursing and midwifery workforce study. Collegian. 2015;22(3):283–9. Tischendorf T, Hasseler M, Schaal T, et al. Developing digital competencies of nursing professionals in continuing education and training - a scoping review. Front Med (Lausanne). 2024;11:1358398. Kleib M, Nagle L. Factors Associated With Canadian Nurses' Informatics Competency. Comput Inf Nurs. 2018;36(8):406–15. Zhou L, Soran CS, Jenter CA, et al. The relationship between electronic health record use and quality of care over time. J Am Med Inf Assoc. 2009;16(4):457–64. Al-Yateem N, Timmins F, Alameddine M, et al. Recruitment of internationally trained nurses: Time for a global model for shared responsibility. J Nurs Manag. 2022;30(7):2453–6. Longhini J, Rossettini G, Palese A. Digital Health Competencies Among Health Care Professionals: Systematic Review. J Med Internet Res. 2022;24(8):e36414. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTable14.docx SupplementaryData.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Digital competence is an extension of information literacy, building upon it and adapting it to the digital age [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Although the concepts overlap, they differ in focus. Information literacy primarily emphasizes computer skills, information literacy, and information management [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In contrast, digital competence focuses on the comprehensive ability to effectively use digital technology across various tasks and contexts. It encompasses not only an understanding of technology but also practical skills and the attitude and behaviors exhibited when interacting with technology [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. As information technology continues to evolve, clinical nurses now spend a significant portion of their time not only providing direct patient care but also mastering the use of electronic health record systems, and they must also be skilled in managing and protecting patient data and proficiently operating telemedicine devices and software to ensure the delivery of efficient and secure healthcare services [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The resulting technological pressures have become a common issue in clinical work environments [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Research has shown that sustained technological pressure can lead to nurse burnout, reduced job satisfaction, and even an increased intention to leave the profession [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Therefore, developing strong digital competence is essential for clinical nurses to fulfill diverse responsibilities in the era of healthcare digital transformation. It supports more effective decision-making, enhances patient safety, and fosters innovation in nursing practice [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe Intensive Care Unit (ICU) is a complex and data-intensive clinical environment, characterized by high clinical workload, making it a critical area for information technology applications [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Critically ill patients generate vast amounts of data, with monitoring equipment at the bedside, such as blood gas analyzers, ventilators, infusion pumps, continuous blood purification devices, and extracorporeal membrane oxygenation, requiring real-time management [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The frequency and scope of clinical monitoring and sampling for these patients far exceed those of regular patients [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Additionally, as digital technologies evolve rapidly, the integration of digital tools into nursing practice has become increasingly profound, raising the demands on ICU nurses' digital competencies to ensure high-quality and efficient care [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. As a result, there is an urgent need for a reliable tool specifically designed to assess the digital skills of ICU nurses, as previous studies have highlighted that organizational support is a key factor in creating a positive digital experience for healthcare professionals, and furthermore, healthcare workers need intrinsic motivation and a willingness to engage with digital tools; innovative solutions to workplace challenges can encourage them to explore the application of digital technologies in ICU settings, thereby fostering the development of their digital capabilities [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Furthermore, relevant studies have identified various factors associated with digital competency levels, including innovation behaviors, educational background, and participation in information technology training [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eInternational research on the digital competencies of healthcare professionals has developed a relatively systematic theoretical framework and practical approaches [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In contrast, studies in China have largely focused on describing the current status of healthcare professionals\u0026rsquo; information literacy and skills, with little progress in developing tools to assess digital competencies [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. To address this gap, our preliminary work introduced the Digital Competence Questionnaire (DCQ), developed by Swiss scholars such as Golz [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], into China, where it was translated, culturally adapted, and psychometrically validated. Building on this foundation, the present study applies the DCQ to assess the digital competencies of ICU nurses, analyzes the factors influencing these competencies, and provides evidence to inform the design of information technology training programs and targeted interventions, with the ultimate goal of improving the quality and effectiveness of nursing care in intelligent healthcare environments.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design\u003c/h2\u003e\u003cp\u003eThis study utilizes a cross-sectional design and employs convenience sampling to select ICU nurses from 5 secondary hospitals and 9 tertiary hospitals in Shandong Province between December 2024 and March 2025.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eParticipant selection and setting\u003c/h3\u003e\n\u003cp\u003eThis study employs an online cross-sectional survey method to collect electronic questionnaire data, ensuring informed consent is obtained. The inclusion criteria for the study population were as follows: (1) aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years; (2) holding a valid nursing license; (3) employed in an ICU for over one year; (4) willing to voluntarily participate in the study with informed consent. The exclusion criteria were as follows: (1) nursing interns or advanced training nurses; (2) nurses absent due to leave or external training. The sample size for multi-factor analysis is typically 10 to 20 times the number of independent variables [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In this study, 12 independent variables were considered. After accounting for a 20% invalid response rate, the required sample size ranged from 150 to 300. A larger sample size allows for a more comprehensive consideration of various factors, enhancing the generalizability and representativeness of the results. In total, 596 questionnaires were collected, with 20 invalid responses excluded, resulting in 576 valid responses and an effective response rate of 96.6%. Ethics(SWYX: NO.2025\u0026thinsp;\u0026minus;\u0026thinsp;239). All participants provided informed consent and voluntarily agreed to participate.\u003c/p\u003e\n\u003ch3\u003eMeasures\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eGeneral Information Questionnaire\u003c/h2\u003e\u003cp\u003eThe design was developed by the research team after reviewing relevant literature and conducting internal discussions. The design includes 11 items: gender, age, education level, marital status, professional title, years of work experience, department, position, hospital type, ICU type, and whether the participant has received training in relevant information technology.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDigital Competence Questionnaire\u003c/h3\u003e\n\u003cp\u003eThe Digital Competence Questionnaire (DCQ) was developed by Swiss scholars Golz et al [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. in 2023 based on the Digital Competence Framework. Building on 26 initial items derived from a prior Delphi study, the questionnaire was further validated through psychometric testing and finalized with 12 items [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Karvouniari et al [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. assessed the reliability and validity of this tool among healthcare personnel in Greece, finding a Cronbach's α of 0.826, which suggests that it is suitable for measuring the digital competence of clinical nurses. Bulut also adapted the DCQ, and the Turkish version has been validated as an effective and reliable tool for assessing nurses' digital competence [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. At the outset of this study, our research team completed the cultural adaptation and revision of the Chinese version of the DCQ [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The Chinese version consists of two dimensions: Knowledge and Skills (6 items) and Attitudes (6 items). Each item uses a 5-point Likert scale, ranging from \"strongly disagree\" to \"strongly agree,\" with scores from 1 to 5. The total score ranges from 12 to 60. Clinical nurses can complete the questionnaire in 3 minutes, and higher scores indicate a higher self-perceived level of digital competence. The overall Cronbach's α value of the questionnaire is 0.970, with Cronbach's α for the individual dimensions ranging from 0.921 to 0.945. The scale's split-half reliability is 0.912, and the test-retest reliability is 0.846.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eCreative Self-Efficacy\u003c/h2\u003e\u003cp\u003eThe Creative Self-Efficacy Questionnaire was developed by Carmeli and Schaubroeck [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] in 2007 and subsequently revised and adapted to the Chinese context by Gu Yuandong [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] and colleagues in 2010. Initially designed for organizational populations, this unidimensional instrument consists of eight items that assess employees\u0026rsquo; confidence in their creative abilities, including completing work tasks, achieving goals, and addressing challenges in innovative ways. Each item is scored on a five-point Likert scale (1 = \u0026ldquo;strongly disagree\u0026rdquo; to 5 = \u0026ldquo;strongly agree\u0026rdquo;), with higher scores reflecting stronger innovative self-efficacy. The original scale demonstrated strong internal reliability, with a Cronbach\u0026rsquo;s alpha of 0.920.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePerecived Organizational Support Scale\u003c/h3\u003e\n\u003cp\u003eThe Perceived Organizational Support Scale was developed by Chen Zhixia [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] in 2006 and revised by Zuo Hongmei [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and colleagues in 2009, resulting in the Nurse Perceived Organizational Support Scale, which has been widely applied in nursing research. The scale comprises 13 items across two dimensions: emotional support (items 1\u0026ndash;10) and instrumental support (items 11\u0026ndash;13). Emotional support represents the encouragement and care offered by the organization, whereas instrumental support denotes the provision of tools and resources required for employees to perform their tasks. Each item is rated on a five-point Likert scale (1 = \u0026ldquo;strongly disagree\u0026rdquo; to 5 = \u0026ldquo;strongly agree\u0026rdquo;), producing a total score between 13 and 65. Higher scores indicate stronger perceived organizational support among nurses. Based on the mean item score, organizational support is categorized into three levels: low (1.00\u0026ndash;2.33), moderate (2.34\u0026ndash;3.66), and high (3.67\u0026ndash;5.00). The scale demonstrates excellent internal consistency, with a Cronbach\u0026rsquo;s alpha of 0.920.\u003c/p\u003e\n\u003ch3\u003eVariable Collection\u003c/h3\u003e\n\u003cp\u003eThis study used the Wenjuanxing platform to conduct a status survey. After obtaining approval from the relevant management departments, the researchers shared the Wenjuanxing link, study purpose, and filling instructions in WeChat and DingTalk groups of ICU departments in various hospitals. ICU nurses anonymously and voluntarily completed the survey. A standardized set of instructions and filling guidelines was provided at the beginning of the questionnaire. To ensure data quality and completeness, submission standards were set on the Wenjuanxing platform, allowing each IP address to submit only one response and requiring all questions to be answered before submission. After data collection, two researchers reviewed the responses to ensure reliability, excluding invalid questionnaires. Questionnaires with excessively short completion times, severe logical inconsistencies, or patterns of answers (e.g., more than 50% of questions answered identically) were discarded.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eData were entered and analyzed using Excel 2019 and IBM SPSS version 29.0(IBM Inc, Armonk, NY, USA). Categorical variables were summarized using frequencies and percentages, while continuous variables conforming to a normal distribution were described as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Comparisons between groups were conducted using independent-samples \u003cem\u003et\u003c/em\u003e tests and one-way analysis of variance (ANOVA). Pearson correlation analysis was employed to examine the relationships among nurses\u0026rsquo; digital competence, innovative self-efficacy, and perceived organizational support. Variables identified as statistically significant in univariate analyses were subsequently included as independent variables in multiple stepwise linear regression models to explore factors influencing digital competence among ICU nurses. Statistical significance was defined as a P value of less than .05.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eGeneral information and digital competence of ICU nurses\u003c/h2\u003e\u003cp\u003eThe results of the univariate analysis in this study indicate that age, education level, hospital tier, and whether nurses have received relevant information technology training are significant factors influencing clinical nurses' digital competence, with statistically significant differences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). These findings are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The total score of the digital competence scale for 576 ICU nurses was 48.58\u0026thinsp;\u0026plusmn;\u0026thinsp;7.02, with an average item score of 4.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73. The attitude dimension scored 24.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.69, with an average item score of 4.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75. The knowledge and skills dimension scored 24.09\u0026thinsp;\u0026plusmn;\u0026thinsp;3.67, with an average item score of 4.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71. In the attitude dimension, the top three items with the highest average scores were Item 4, Item 2, and Item 6. In the Knowledge \u0026amp; Skills dimension, the top three items with the highest average scores were Item 10, Item 12, and Item 11, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eUnivariate Analysis of Demographics and Digital Competence of ICU Nurses (n\u0026thinsp;=\u0026thinsp;576)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en(%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDigital Competence Score(x\u0026thinsp;\u0026plusmn;\u0026thinsp;s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003et/F\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-1.213\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.225\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e126(21.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e49.25\u0026thinsp;\u0026plusmn;\u0026thinsp;8.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e450(78.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.40\u0026thinsp;\u0026plusmn;\u0026thinsp;6.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.149\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e93(16.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e49.10\u0026thinsp;\u0026plusmn;\u0026thinsp;7.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e326(56.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.60\u0026thinsp;\u0026plusmn;\u0026thinsp;6.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e36\u0026ndash;45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e147(25.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.46\u0026thinsp;\u0026plusmn;\u0026thinsp;7.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10(1.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e45.00\u0026thinsp;\u0026plusmn;\u0026thinsp;11.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.266\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e355(61.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.42\u0026thinsp;\u0026plusmn;\u0026thinsp;7.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnmarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e214(37.15)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.97\u0026thinsp;\u0026plusmn;\u0026thinsp;6.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWidowed/divorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7(1.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e45.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducational level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.557\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary and tertiary education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37(6.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e47.38\u0026thinsp;\u0026plusmn;\u0026thinsp;10.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUndergraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e486(84.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.53\u0026thinsp;\u0026plusmn;\u0026thinsp;6.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGraduate and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e53(9.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e49.94\u0026thinsp;\u0026plusmn;\u0026thinsp;5.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProfessional Title\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.411\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.663\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e321(55.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.64\u0026thinsp;\u0026plusmn;\u0026thinsp;7.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntermediate level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e234(40.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.40\u0026thinsp;\u0026plusmn;\u0026thinsp;7.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdvanced level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e21(3.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e49.81\u0026thinsp;\u0026plusmn;\u0026thinsp;6.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYears of work (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.581\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.559\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e240(41.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.92\u0026thinsp;\u0026plusmn;\u0026thinsp;6.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u0026ndash;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e202(35.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.56\u0026thinsp;\u0026plusmn;\u0026thinsp;6.84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e134(23.26)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.20\u0026thinsp;\u0026plusmn;\u0026thinsp;7.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eJob Position\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.754\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.154\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eClinical Nurse\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e389(67.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.64\u0026thinsp;\u0026plusmn;\u0026thinsp;6.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing administrator\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e89(15.45)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.07\u0026thinsp;\u0026plusmn;\u0026thinsp;6.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNursing Team Leader\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e52(9.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e50.46\u0026thinsp;\u0026plusmn;\u0026thinsp;5.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e46(7.99)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e47.40\u0026thinsp;\u0026plusmn;\u0026thinsp;8.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHospital level (tier)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e5.883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTertiary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e519(90.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.71\u0026thinsp;\u0026plusmn;\u0026thinsp;6.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e57(9.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.06\u0026thinsp;\u0026plusmn;\u0026thinsp;6.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eICU type\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.382\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.820\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpecialized ICU\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e153(26.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e48.90\u0026thinsp;\u0026plusmn;\u0026thinsp;5.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eComprehensive ICU\u003c/p\u003e\u003cp\u003eReceived relevant information training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e423(73.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e47.66\u0026thinsp;\u0026plusmn;\u0026thinsp;5.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e370(64.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e49.88\u0026thinsp;\u0026plusmn;\u0026thinsp;6.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e206(35.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e46.26\u0026thinsp;\u0026plusmn;\u0026thinsp;6.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRanking of digital competency scores of ICU nurses(N\u0026thinsp;=\u0026thinsp;576)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems related to digital competency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRank\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eScore\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAttitude\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4.I believe that digital technology provides numerous benefits in terms of quality of care.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.82\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2.I enjoy using digital technology at my workplace.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6.I believe that digital technology is beneficial for my patients.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3.I like to use digital technology at work.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5.I believe that digital technology improves patient outcomes.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1.Digital technology fits well with the way I like to work.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eKnowledge \u0026amp; Skills\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e4.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10.I feel confident about using digital technology to obtain data and information on clinical care.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.67\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12.I feel confident in dealing with confidentiality issues relating to digital technology at my workplace.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11.I am able to reach conclusions based on information acquired through digital technologies.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.69\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9.I feel confident about using digital technology to communicate.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8.I feel confident about using digital technology to find relevant information.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e4.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7.I am familiar with the digital technologies at my workplace.\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e3.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.75\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eAnalysis of ICU nurses' digital competence and its relationship with innovation self-efficacy and organizational support\u003c/h2\u003e\u003cp\u003eA total of 576 ICU nurses were surveyed to analyze their digital competence and its relationship with innovation self-efficacy and organizational support. The average scores for innovation self-efficacy and organizational support were 30.75\u0026thinsp;\u0026plusmn;\u0026thinsp;6.25 and 54.54\u0026thinsp;\u0026plusmn;\u0026thinsp;7.07, respectively. The emotional support dimension scored 41.28\u0026thinsp;\u0026plusmn;\u0026thinsp;6.17, while the instrumental support dimension scored 8.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.80. The analysis confirmed that the innovation self-efficacy, organizational support, and their respective dimensions of the nurses all passed normality tests. Pearson correlation analysis indicated that digital competence was positively correlated with innovation self-efficacy (r\u0026thinsp;=\u0026thinsp;0.472, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and organizational support (r\u0026thinsp;=\u0026thinsp;0.319, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, positive correlations were observed between digital competence and both the emotional and instrumental support dimensions (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Refer to Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelational Analysis of ICU Nurses' Digital Competency, Innovative Self-Efficacy, and Perceived Organizational Support (N\u0026thinsp;=\u0026thinsp;576)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eItems\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eScore(x\u0026thinsp;\u0026plusmn;\u0026thinsp;s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003er\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCreative Self-Efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e30.75\u0026thinsp;\u0026plusmn;\u0026thinsp;6.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerecived Organizational Support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e\u003cp\u003e54.54\u0026thinsp;\u0026plusmn;\u0026thinsp;7.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.319\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eNotes r: Correlation Coefficients with ICU Nurses' Digital Competency\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eMultiple linear regression analysis of ICU nurses' digital competence\u003c/h2\u003e\u003cp\u003eThe total score of ICU nurses' digital competence was set as the dependent variable, while variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in univariate analysis, along with organizational support and innovation self-efficacy, were selected as independent variables for stepwise regression. The inclusion criteria were p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and the exclusion criteria were p\u0026thinsp;\u0026gt;\u0026thinsp;0.05. The assignment method for the independent variables is shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, with the raw scores of the innovation self-efficacy and organizational support scales directly used. The analysis revealed that education level, hospital tier, years of service\u0026thinsp;\u0026ge;\u0026thinsp;6, organizational support, and innovation self-efficacy were positive predictors of digital competence, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eAssignment methods of independent variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNotation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAllocation method\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAge(years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;25\u0026thinsp;=\u0026thinsp;1; 25\u0026ndash;35\u0026thinsp;=\u0026thinsp;2; 36\u0026ndash;45\u0026thinsp;=\u0026thinsp;3; \u0026gt;45\u0026thinsp;=\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducational level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSecondary and tertiary education\u0026thinsp;=\u0026thinsp;1; Undergraduate\u0026thinsp;=\u0026thinsp;2; Graduate and above =\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHospital level (tier)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTertiary\u0026thinsp;=\u0026thinsp;1; Secondary\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eX4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eReceived relevant information training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u0026thinsp;=\u0026thinsp;1; No\u0026thinsp;=\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultiple linear regression analysis of the factors influencing ICU nurses' digital competence (n\u0026thinsp;=\u0026thinsp;576)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eB Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eStandard error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003et value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eVIF\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28.717\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.899\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e2.408\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.906\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducational level\u003c/p\u003e\u003cp\u003eHospital level (tier)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.089\u003c/p\u003e\u003cp\u003e0.122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.301\u003c/p\u003e\u003cp\u003e1.118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003cp\u003e0.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.974\u003c/p\u003e\u003cp\u003e3.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.049\u003c/p\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.014\u003c/p\u003e\u003cp\u003e1.023\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eReceived relevant information training\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.597\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.123\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.891\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.018\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCreative Self-Efficacy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.546\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.041\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.050\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e8.417\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.007\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerecived Organizational Support\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.142\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.019\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"8\"\u003e\u003cb\u003eNotes\u003c/b\u003e F\u0026thinsp;=\u0026thinsp;45.142, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.284, adjusted R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.277. VIF: Variance inflation factor\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eOverall digital competence of ICU nurses was above average\u003c/h2\u003e\u003cp\u003eThe results of this study indicate that the total score for digital competence among 576 ICU nurses was 48.58\u0026thinsp;\u0026plusmn;\u0026thinsp;7.02, with an average item score of 4.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73, reflecting a moderately high level of digital competence. These findings are consistent with those of Karvouniari et al.,\u003csup\u003e26\u003c/sup\u003e who conducted a cross-sectional study on 494 healthcare professionals. However, with the rapid development of artificial intelligence (AI) technologies in the healthcare field, such as intelligent diagnostics, telemedicine, and personalized treatment recommendations, the demands on nurses' digital competence are increasing. The role of nurses is expected to evolve from mere executors of tasks to bridges between technology and humanistic care. Nurses will not only need to possess fundamental medical and nursing skills but also be proficient with new technological tools to ensure they can play a crucial role in highly digitized healthcare environments. Therefore, ICU nurses' digital competence, particularly in the application of AI technologies, will directly influence the quality of healthcare services and patient treatment outcomes.\u003c/p\u003e\u003cp\u003eIn the two dimensions investigated in this study, the attitude dimension scored higher, while the knowledge and skills dimension scored lower. This suggests that ICU nurses generally possess a positive attitude and confidence regarding digital competence but still face challenges in mastering the knowledge and skills necessary for the practical application of digital technologies. Konttila et al [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], also highlighted that the digital competence of healthcare professionals is closely related to clinical knowledge and skills, and digital competence should be seen as an integral part of everyday activities. This phenomenon may reflect the fact that while ICU nurses acknowledge and accept the importance of digital technologies, they encounter difficulties and limitations in acquiring practical operational skills and applying them effectively in their work.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eICU nurses with a stronger sense of organizational support demonstrate higher levels of digital competence\u003c/h2\u003e\u003cp\u003eMultiple linear regression analysis showed that organizational support significantly influences the digital competence of ICU nurses (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A positive correlation was also found between perceived organizational support and digital competence (r\u0026thinsp;=\u0026thinsp;0.319, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Organizational support acts as a catalyst for developing digital competence by integrating managerial support, adequate resources, and a culture that values technological innovation [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Supportive leadership enhances nurses\u0026rsquo; motivation to acquire digital skills by clarifying the practical value of technologies (e.g., electronic health records, wireless monitoring systems) and reducing operational barriers [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. When institutions allocate time for training and encourage feedback on system usability, nurses\u0026rsquo; confidence in digital platforms improves, even in the high-risk and time-sensitive ICU environment. Adequate resources, including reliable infrastructure, continuous educational programs, and technical support, further provide the foundation for competence development. Conversely, limited equipment access or fragmented training (e.g., one-time workshops without follow-up) can cause frustration and reduce tool utilization [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In addition, a collaborative organizational culture characterized by knowledge sharing and recognition of digital proficiency sustains competence over time, and mentoring by experienced nurses and acknowledgment of successful technology-driven interventions strengthen the overall digital competence of ICU teams [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. This finding aligns with research showing that a positive team climate\u0026mdash;marked by support for innovation and participative safety\u0026mdash;correlates with healthcare professionals\u0026rsquo; motivation to adopt digital technologies [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. In the ICU, such a culture is especially critical, as it ensures the rapid and accurate use of digital data in life-saving decisions. In summary, the synergy of leadership, resources, and culture enables organizational support to act as a \u0026ldquo;multiplier\u0026rdquo; of nurses\u0026rsquo; digital competence, transforming technical access into practical skills and ensuring that digital tools effectively serve both patient care and professional development.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eICU nurses with higher levels of innovative self-efficacy generally demonstrate greater digital competence\u003c/h2\u003e\u003cp\u003eInnovative self-efficacy, a psychological factor, significantly affects the digital competence of ICU nurses (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). It refers to an individual's confidence in overcoming challenges and successfully applying new technologies or methods independently [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In our study, ICU nurses' innovative self-efficacy is strongly associated with their digital skills performance (r\u0026thinsp;=\u0026thinsp;0.472, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Nurses with higher innovative self-efficacy are more likely to actively adopt and master emerging digital tools and technologies, such as electronic health records and patient monitoring devices [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Additionally, they typically exhibit strong learning abilities and adaptability to new technologies, making them more proactive and effective in using and learning digital tools, and they proactively adopt and apply new nursing techniques while adapting flexibly to challenges in practice, thereby improving both work efficiency and patient care quality [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. This self-efficacy likely arises from nurses' understanding of new technologies, their learning attitudes, and accumulated hands-on experience. When nurses believe in their ability to effectively use new technologies, their digital competence improves as well. Therefore, cultivating and enhancing ICU nurses' innovative self-efficacy not only increases their acceptance of digital technologies but also improves their practical application skills, driving the digital transformation of ICU nursing services.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eEnhanced Information Technology Training Improves ICU Nurses' Digital Competence\u003c/h2\u003e\u003cp\u003eThis study demonstrated that ICU nurses with information technology training achieved significantly higher scores in overall digital competence and all its dimensions than their untrained counterparts. Consistent with prior research [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], these findings underscore the critical role of structured, systematic training in narrowing the digital gap among healthcare providers and offer empirical support for hospitals and nursing education institutions in developing training protocols. A systematic review [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] further confirmed that multi-modal interventions in digital competency training for nurses and other healthcare providers significantly enhance digital proficiency. Regular training and simulation exercises, for instance, improve nurses' ability to apply information technologies in clinical practice\u0026mdash;including electronic health record systems, telemedicine platforms, and patient management software. As the healthcare sector grows increasingly dependent on information technology, nurses' digital competency will become a pivotal factor in enhancing healthcare service quality. Consequently, hospital and nursing administrators should recognize digital competency training as a long-term strategic investment rather than a short-term obligation. Training strategy development should extend beyond basic operational proficiency to focus on establishing a hierarchical, multi-dimensional, and sustainable progressive training framework [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Additionally, establishing standardized technical support and feedback mechanisms, conducting regular evaluations of training efficacy, and updating training content based on clinical demands and technological progress are critical to sustaining the development of ICU nurses' digital competency and their capacity to address future technological challenges effectively.​\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eEducational background and hospital level are other factors influencing ICU nurses' digital competence\u003c/h2\u003e\u003cp\u003eOur analysis indicates that educational background significantly impacts ICU nurses' digital competence (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049). ICU nurses with a bachelor's degree or higher demonstrate significantly higher digital competence than those with a diploma, consistent with the findings of Kleib et al [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Nurses with higher education are more likely to have received training in literature and information retrieval, leading to more comprehensive learning and development. However, the small number of graduate-degree nurses in this study may limit the generalizability of our findings. Additionally, ICU nurses with higher education levels tend to have stronger intrinsic motivation to learn and adapt to new technologies, and they are more likely to actively master digital tools to support clinical decision-making and nursing practices, demonstrating higher digital competence [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Therefore, hospital administrators should prioritize continuing education and career development for nursing staff by designing tiered, targeted programs to improve digital competence for ICU nurses with varying educational backgrounds. For example, diploma nurses could receive basic information technology training, while nurses with a bachelor's degree or higher should focus on data analysis and advanced information systems applications, advancing the implementation of nursing informatization.\u003c/p\u003e\u003cp\u003eICU nurses in tertiary hospitals (48.71\u0026thinsp;\u0026plusmn;\u0026thinsp;6.94) score higher in digital competence than those in secondary hospitals (48.06\u0026thinsp;\u0026plusmn;\u0026thinsp;6.58). Higher-level hospitals set higher competency expectations for ICU nurses and focus more on enhancing their skills during advanced stages of professional development. Enhancing digital competence helps ICU nurses maintain a continuous learning drive throughout their careers [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Moreover, tertiary hospitals often introduce digital systems, such as electronic health records, clinical decision support systems, and remote monitoring facilities, earlier. Nurses in these hospitals frequently interact with these systems in their daily work, continuously reinforcing and enhancing their digital application skills [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Therefore, it is recommended that secondary and lower-level healthcare institutions increase investments in IT infrastructure, optimize digital training resources, and establish learning exchange mechanisms with higher-level hospitals. This will help reduce the digital competence gap between ICU nurses in different hospitals and enhance the overall information literacy of the nursing workforce.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis study has several limitations that should be acknowledged. First, as a cross-sectional study, it can only demonstrate associations rather than causal relationships between ICU nurses\u0026rsquo; digital competence and its influencing factors, such as organizational support and innovative self-efficacy. Second, the use of a convenience sampling method in a single province (Shandong) may limit the generalizability of the findings to other regions or healthcare systems with different technological infrastructures or training practices. Third, the data were collected through self-reported questionnaires, which may be subject to recall bias and social desirability effects, potentially leading participants to overestimate their digital competence. Additionally, although validated measurement tools were employed, unmeasured confounding variables\u0026mdash;such as workload intensity, institutional digital maturity, and prior exposure to digital health systems\u0026mdash;might also have influenced the results. Future studies should adopt longitudinal or mixed-method designs, expand sampling across multiple provinces or countries, and incorporate objective assessments of digital competence to further validate and refine these findings.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study revealed the current state of digital competence among ICU nurses and analyzed its influencing factors. The results indicate that innovation self-efficacy, organizational support, as well as factors such as nurses' educational background and hospital tier, are positively correlated with digital competence. Specifically, higher levels of innovation self-efficacy and stronger organizational support significantly enhance ICU nurses' digital competence. These findings provide a solid foundation for developing targeted digital competence training and intervention strategies. Future research should further explore how to optimize training models and improve nurses' ability to use digital tools effectively in high-pressure environments, thus promoting the digital transformation of ICU nursing practice. Additionally, cross-regional and longitudinal studies will help validate the generalizability of these findings and provide deeper insights into the development of digital health services.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003e The study was approved by the Ethics Committee of the Affiliated Provincial Hospital of Shandong First Medical University (Approval Number: SWYX: NO.2025\u0026thinsp;\u0026minus;\u0026thinsp;239) and was conducted in accordance with the Helsinki Declaration. All participants provided written informed consent and were thoroughly briefed on the study's objectives, as well as the confidentiality and anonymity of their personal information. Additionally, they were assured that their participation was entirely voluntary and that they could withdraw from the study at any stage without consequence.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (NSFC) (grant number: 61861047); and the Nursing Research Project of Shandong Provincial Hospital (grant number: HL2025-32); Technology Project the China International Medical Foundation (grant number: 2-2018-35-2004).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eZW designed the study, collected and analyzed data, interpreted results, and drafted the manuscript. CL and JZ revised the manuscript. XW analyzed data and contributed to the manuscript. CF, ZZ, YS, and MJ assisted in data collection. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e\u003cp\u003eWe would like to express our sincere gratitude to Professor Christoph Golz for providing the original version of the questionnaire during the early stages of the Chinese adaptation process. His support was invaluable throughout the adaptation and subsequent research stages. Additionally, we would like to thank all the participants who contributed to this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCouncil of the European Union. 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J Nurs Manag. 2022;30(7):2453\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLonghini J, Rossettini G, Palese A. Digital Health Competencies Among Health Care Professionals: Systematic Review. J Med Internet Res. 2022;24(8):e36414.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Digital competence, ICU nurses, Organizational support, Innovative Self-Efficacy, Influencing factors","lastPublishedDoi":"10.21203/rs.3.rs-7851326/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7851326/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eDigital competence builds upon information literacy, extending and expanding it in the digital age. The ICU is characterized by complex, data-intensive environments and high clinical workload, making it a critical setting for the application of information technology. At the same time, the integration of nursing practice with digital tools and technologies is deepening, placing greater demands on ICU nurses' digital competence.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo investigate the digital competence of ICU nurses and analyze the relevant influencing factors, providing valuable insights for the development of personalized intervention strategies.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis study employed a cross-sectional design. From December 2024 to March 2025, a convenience sampling method was used to survey 576 ICU nurses in Shandong Province. Data were collected using general information questionnaires, the Digital Competence Scale, the Organizational Support Scale, and the Innovation Self-Efficacy Scale. Univariate analysis, Pearson correlation analysis, and multiple linear regression analysis were conducted to explore the factors influencing the digital competence of ICU nurses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe total score on the Digital Competence Scale was 48.58\u0026thinsp;\u0026plusmn;\u0026thinsp;7.02, with an average item score of 4.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73. Innovation self-efficacy (r\u0026thinsp;=\u0026thinsp;0.472, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and organizational support (r\u0026thinsp;=\u0026thinsp;0.319, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly positively correlated with digital competence. Multiple linear regression analysis indicated that gender, whether the nurse had received relevant information technology training, innovation self-efficacy, and organizational support were significant factors influencing digital competence among clinical nurses (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eAlthough ICU nurses demonstrate a positive attitude toward digital technologies, there remains a significant gap in their practical skills and knowledge application. With the increasing use of digital tools in healthcare, enhancing ICU nurses' digital skills is crucial for improving nursing quality and patient outcomes. Future research should focus on long-term digital competence development programs and explore additional factors influencing the practical application of these skills, further advancing the digital transformation of clinical nursing practice.\u003c/p\u003e","manuscriptTitle":"Current status and influencing factors of digital competence among nurses in intensive care units: a cross-sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-07 12:12:12","doi":"10.21203/rs.3.rs-7851326/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d5ba6b30-c012-4d58-9218-0205f06d5089","owner":[],"postedDate":"November 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-02T11:59:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-07 12:12:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7851326","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7851326","identity":"rs-7851326","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}