Abstract
Background
In the information age of health care, nurses often face information overload, leading to negative emotions, e.g., anxiety that may impede the adoption of evidence-based practice and clinical decision-making process. Nurses with higher digital health literacy can effectively process and manage information. Despite this, no research has explored the relationship between information anxiety, digital health literacy, and core competency among nurses. Therefore, this study aims to investigate the mediating effects of digital health literacy on information anxiety and core competency among nurses.
Methods
From July to October 2023, the data for this cross-sectional study were collected. The study surveyed a total of 608 nurses from three tertiary hospitals in Fujian Province, and the survey instruments included a sociodemographic information questionnaire, Chinese revision version of the Digital Health Literacy Instrument (CR-DHLI), Information Anxiety Scale (IAS), and Competency Inventory for Registered Nurses (CIRN). Descriptive statistics and Pearson correlation analysis were conducted using SPSS 29.0, and the mediating effect of digital health literacy was examined using Mplus.
Results
The mean score of nurses’ information anxiety, digital health literacy, and core competency was 3.03 ± 0.91, 2.46 ± 0.56, 2.72 ± 0.88, respectively. And the mediation model of information anxiety on core competency for nurses showed a good model fit index (χ²/df = 2.207, CFI = 0.985, TLI = 0.982, RMSEA = 0.045, SRMR = 0.035). Digital health literacy was positively correlated with nurses’ core competency but negatively correlated with information anxiety. The results of path analysis revealed that information anxiety had negative and significant direct effects on NCC (β = -0.119, P = 0.004) and DHL (β = -0.297, P < 0.001). DHL had a positive effect on NCC (β = 0.306, P < 0.001). Digital health literacy played a partial mediating role, accounting for 43.54% of the relationship between information anxiety and nurses’ core competency.
Conclusions
Information anxiety among nurses was at relatively high levels, which had a negative impact on the core competency of nurses. This issue requires attention from nursing managers. The mediating role of digital health literacy in the relationship between information anxiety and core competency among nurses has been established. Nursing managers should strengthen the evaluation of nurses’ DHL and devise effective support strategies to enhance DHL, thus improving the core competence of nurses in information age.
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Advances in information and communication technologies (ICTs) have accelerated the digitization of health care fields [1]. ICTs refer to all communication technologies, including the internet, wireless networks, computers, video-conferencing, social networking, and other media applications and services for which enabling users to access, retrieve, store, transmit, and manipulate information in a digital form, etc. [2]. The evolution of health care from the “face-to-face age” to the “information age” has been profoundly influenced by the emergence of ICTs [3]. The impact of ICTs on the nursing practice is being recognized by nurses [4]. The use of ICTs is not only for transmitting information but also for supporting self-care and offering benefits in tracking chronic disease patients [5,6,7]. The digital transformation of healthcare is giving new vitality to improving the quality of care and health outcomes [8]. Nurses must adjust to this new context to remain relevant and effective, this requires a shift in the epistemology of professional nursing to recognize the digital environment in which care is provided [9]. There is increased attention to nurses’ core competency (NCC) in complex digital health care setting.
Core competency of registered nurses
The core competency of registered nurses refers to the professional ability shown in the completion of nursing works, including knowledge, skills, attitudes, values and other comprehensive abilities [10, 11]. NCC is a holistic and dynamically evolving competency, involves the integration of multiple abilities in response to changes in society, healthcare environments, and the nursing profession [12]. Liu et al. [10, 13] developed the Competency Inventory for Registered Nurses (CIRN) in China based on International Council of Nurses (ICN) Framework of Competencies for the Generalist Nurse proposed by the ICN. This framework includes competencies in clinical care, leadership, interpersonal relationship, legal/ethical practice, professional development, teaching-coaching, critical thinking/research aptitude [10, 13]. In this study, NCC signifies the application of knowledge, skills, and attitudes by nurses in clinical practice, enabling individuals to effectively perform a range of tasks and adhere to appropriate standards to adapt to the continuously evolving social, medical environment, and nursing profession [12]. The process of digitization will result in substantial alterations to the roles and duties of the healthcare personnel, hence underscoring the necessity for capacity building and continuous professional development [14]. Digital technologies are increasingly being employed in the healthcare sector, offering new avenues for nurses to care for patients, conduct research and education, track diseases, and monitor public health [3, 9, 15]. When integrated with clinical practices and tailored to fit these practices, ICTs can be effectively utilized, transforming the internet into a convenient digital information resource for busy nursing professionals [16, 17]. This supports the professional development of healthcare personnel [18]. And previous study [19] indicate that proficient users of ICTs exhibit higher nursing abilities compared to those with lower ICTs skills. In essence, ICTs empowers nurses to enhance their core competencies by leveraging technology to improve patient care, streamline operations, foster collaboration, and advance professional development within the rapidly evolving healthcare landscape. The abilities to generate, send, and process information are recognized as practical skills influencing nursing capacity in such a digital healthcare environment [20]. This implies that the ability to gather, process and send information as well as other skills relating to ICT, exert an influence on nursing competency [19]. Therefore, when nurses encounter difficulties and uncertainties while using ICTs, they are prone to negative emotions [21], which may affect their core competencies.
Information anxiety
Individuals may experience anxiety when they come to the realization that they lack the ability to comprehend perceived information [22, 23]. Wurman proposed that “Information anxiety is produced by the ever-widening gap between what we understand and what we think we should understand” [24]. The information generated within the healthcare sector, as well as information pertaining to healthcare, has experienced exponential growth with the advent of the World Wide Web (www) and online communication [22]. Registered nurses hold a distinctively crucial role in the provision of medical services, to stay current with professional advancements and navigate the swiftly evolving, multifaceted realm of medical practice, they consistently require access to information to supplement their knowledge and clinical experience [25, 26]. However, accessing and processing a vast amount of information within a limited time frame can prove burdensome and stressful, leading to information overload [27]. The increase in health information technology is supposed to improve nursing quality, efficiency, and safety. However, information overload in electronic health records has been shown to detract from the ease of use of the system, contribute to stress and burnout among healthcare professionals, worsen workloads, and create opportunities for errors [28,29,30]. Previous studies [31, 32] pointed out that when faced with a health crisis such as COVID-19, it generated a deluge of information [33, 34], which impeded nurses’ ability to process the information accurately leading to subpar decision-making. The information on the internet is complex, chaotic and of varying quality, while users have a strong psychological reaction to the reliability of information, inaccurate or duplicated information often compels nurses to spend a significant amount of time collecting and utilizing data, leading to they have strong irritability and anxiety. Persistent exposure to anxiety may have adverse effects on their behavior patterns, psychological states and work performance [35,36,37]. It has been shown that although a certain level of anxiety can be beneficial for motivating and arousing enthusiasm in an individual, unmanaged anxiety can have long-term consequences on the work performance and job satisfaction of nurses [38, 39]. Earlier study [40] have found that when nurses are uncertain about the relevance, accuracy, or effective application of information, or when they feel overwhelmed by the volume and complexity of research evidence, the information overload or anxiety can impede evidence-based practice (EBP) and clinical decision-making in the context of nursing.
Digital health literacy
Previous study [41] has shown that digital health literacy (DHL) contributes to alleviating the adverse consequences (e.g., information anxiety) of the infodemic (an infodemic is too much information including false or misleading information, in digital and physical environments during a disease outbreak [42]). DHL, refers to “the ability to search, select, appraise, and apply online health information and health care-related digital applications” [43, 44]. Studies [45,46,47] have shown that high DHL contributes to nurses’ ability to effectively navigating the healthcare system web-based for information retrieval and decision-making, enabling them to accurately comprehend and utilize essential data to enhance nursing competency and medical service. DHL has evolved into an essential skill for health professionals, enabling them to find accurate and reliable health information online, improved skill development is probably going originate from valuable medical internet research chances that foster critical thinking [48, 49], ensuring that individuals are optimally making use of available digital health access. Poor digital health literates might suffer more from information overload. Indeed, study has underlined the significance of strengthening DHL level to cope with information overload [50]. Previous study [51] showed DHL can mitigate the heightened psychological distress elicited by the infodemic. Furthermore, Kim et al. [52] found that online misinformation leads to misunderstandings regardless of DHL levels. However, individuals with higher DHL are better equipped to verify and correct these misunderstandings, making them less likely to act on them. This indicates that DHL is crucial for helping individuals navigate environments with information overload.
Theoretical framework and research hypotheses
The hypothesized model (Fig. 1) of this study was derived from the Transactional Model of eHealth Literacy (TMeHL) developed by Paige [53]. TMeHL highlights the role of DHL in empowering individuals and facilitating informed decision-making. This is particularly relevant for nurses who need to be adept at using digital health information to make critical clinical decisions and provide patient care. TMeHL assumes that contextual factors affecting DHL were divided into task-oriented and user-oriented factors. The interaction of these factors produces different degrees and types of noise factors, which hinder or promote the successful interaction of online health information [53]. However, the opposite association exists between DHL and the detrimental impact of noise. And greater DHL levels counteracts the adverse effects of noise generated by digital health contextual factors and facilitates a favorable digital health experience and translational (application) competency [53]. In this study, the proposed conceptual model consists of three concepts: (1) the noise refers to information anxiety, including cognitive or information overload due to a wide variety of multimedia or physical challenges with the technology used or the affective response to the eHealth experience, including the urgency of the information or the nature of the search. (2) DHL, a multidimensional and hierarchical individual skill, as conceptualized by TMeHL. (3) Informed and empowered: the capacity of an informed and engaged user to apply knowledge gained from a digital health transaction across diverse socioecological factors will ultimately inform users’ future digital health motivation and perceived usefulness for addressing a particular health concern. For nurses, this empowerment refer to effective patient care, clinical decision-making, and professional development. According to the TMeHL, DHL mediates the relationship between the effect of noise on digital health contextual factors and the degree to which a digital health end user is informed and empowered. Based on the model, we hypothesized that DHL may play a mediating role between information anxiety and core competency. Therefore, based on previous studies and TMeHL, we constructed a research model with information anxiety as the independent variable, NCC as the dependent variable, and DHL as mediating variable (Fig. 1). We proposed the following three hypotheses:
Hypothesis 1
information anxiety is significantly and negatively related to NCC.
Hypothesis 2
DHL is significantly and positively related to NCC.
Hypothesis 3
DHL mediates the relationship between information anxiety and NCC.
The purpose of this study was to investigate the correlation between information anxiety and NCC, and investigate the mediating role of DHL in this relationship in particular. To the best of our knowledge, this study is the first to examine the relationship between DHL, information anxiety, and NCC. This study provides valuable insights into how information anxiety affect nursing performance and the role that digital health literacy plays in this relationship. By understanding these dynamics, nursing managers can implement targeted interventions, training programs, and policies that enhance nurses’ competencies, reduce anxiety, and ultimately improve patient care.
Methods
Study design and participants
A cross-sectional survey was conducted in Fujian Province, China. From July to October 2023, eligible nurses from the 3 selected tertiary hospitals located in Western Fujian (Longyan), Central Fujian (Fuzhou), and Southern Fujian (Quanzhou) were included using convenience sampling. Inclusion criteria were: (a) being a registered nurse and being employed at the hospital; and (b) volunteering to participate in the study. The exclusion criteria were as follows: (a) work less than 6 months; (b) absence due to illness, maternity, or other personal reasons for more than 6 months. The relationship between information anxiety, DHL, and NCC was analyzed using a structural equation model (SEM), requiring a minimum of 200 samples to run the model, as suggested by Shah and Goldstein [54]. And the suggested empirical power tables based on study by Fritz and Mackinnon [55], a sample size of 558 or greater is required for 0.8 power when using the percentile bootstrap to test the mediating effect [56]. A total of 656 nurses completed and returned the surveys. However, 48 questionnaires were disqualified due to irregular responses and were excluded from the overall analysis. As a result, 608 nurses participated in the study, with a response rate of 92.68%.
Measurement
Four tools were used to collect data and analyze the variables of this study:
-
1.
Socio-demographic characteristics
Socio-demographic information collected included age, gender, educational background, years of nursing experience, professional title, working position (general nurse, clinical nursing teachers, nursing team leader, head nurse), average monthly earnings (CNY), form of employment (contract nurses or official nurses), official nurses are hired for a job position to work stably and continuously, covered by the social insurance system of health care institutions, with good benefits than contract nurses in China [57].
-
2.
Digital health literacy instrument (DHLI)
The DHLI [44] was used to assess DHL. The DHLI was developed by van der Vaart and Drossaert [44] and translated into Chinese version (CR-DHLI) by Zhao et al [58]. CR-DHLI is comprised of 7 subscales: (1) operational skills; (2) navigation skills; (3) information searching; (4) determining relevance; (5) evaluating reliability; (6) adding self-generated context; (7) protecting privacy and 7 performance-based items [44, 58]. Each self-reported item was scored on a Likert 5-point scale with scores ranging from 0 (very difficult) to 4 (very easy) and 0 (never) to 4 (often), each performance-based item has 4–5 answer options, of which 1 is correct, correct answer receives 1 point, accumulating a maximum of 7 points in total. The mean of subscales was used to calculate DHL total score, the higher the score, the greater the DHL. The validity and reliability of the CR-DHLI was approved, the Cronbach’s alpha coefficient was calculated to be 0.929 in the study of Zhao et al [58]. In this study, the Cronbach’s alpha was 0.947.
-
3.
Information anxiety scale (IAS)
To access information anxiety, the IAS was used [59], It consists of 30 items. Each item response is rate on Likert 5-point scale with scores ranging from 1 (strongly disagree) to 5 (strongly agree). It has 6 subscales: (1) information quality anxiety; (2) information quantity anxiety; (3) information retrieval tool anxiety; (4) information literacy anxiety; (5) information acquisition anxiety; and (6) information processing anxiety. An increased score signifies a more severe degree of information anxiety. Cronbach’s alpha coefficient of IAS in the original study was calculated to be 0.972 [59]. In the present study, the Cronbach’s alpha value was 0.984.
-
4.
Competency inventory for registered nurses (CIRN)
Nurse’s core competency was accessed by the CIRN [10]. It consists of 55 items. Each item response is rate on Likert 5-point scale with scores ranging from 0 (not competent at all) to 4 (very competent). It has 7 subscales: (1) clinical care; (2) leadership; (3) interpersonal relationship; (4) legal/ethical practice; (5) professional development; (6) teaching-coaching; (7) critical thinking/research aptitude [10]. A higher score corresponds to a greater NCC. The Cronbach’s alpha coefficient for this scale has been in the range of 0.90 to 0.97 in current studies [10, 60, 61], and it has been psychometrically evaluated and implemented in different countries. The Cronbach’s alpha value was 0.988.
Data collection
The data for the study were gathered via an online questionnaire survey platform (accessible at www.wjx.cn), utilizing an innominate, self-reported questionnaire. Initially, we contacted three hospital administrators in Fujian province via WeChat, requesting their assistance in distributing the web-based survey link to their nurse staff who met the criteria. With the cooperation of nursing managers, the questionnaires were successfully distributed to the nurses. Participants were acquainted about the purpose, significance, and precautions of the survey process. Those who voluntarily chose to take part in the study completed the questionnaire by either clicking on the provided link on WeChat or scanning the QR code. To ensure the completeness and validity of the questionnaire, we adhered to unified guidelines, designated all questions as mandatory, restricted each IP address to one submission only, and established a minimum cumulative answer time of 200 s. One week before the survey, the primary researcher provided training to other worker. These trained researchers were responsible for collecting the online questionnaires and monitoring the quality of responses throughout the process. In the event of any issues, researchers communicated with the nursing managers of each hospital for resolution.
Data analysis
Data were analyzed using IBM SPSS Statistics 29.0 software and Mplus version 8.0. Normally distributed continuous variables were expressed as the mean and standard deviations (SD), nonnormally distributed continuous variables were presented as the median and interquartile range (IQR). The relationship among information anxiety, DHL, and NCC was verified using the Pearson correlation test. The mediating effect of DHL in the relationship between information anxiety and NCC was estimated using the structural equation modeling method implemented in Mplus 8.0. The covariance matrix of relevant variables was evaluated by maximum likelihood (ML) estimation. We applied 5,000 samples for bootstrap resampling and a 95% confidence interval (CI) to examine the direct and indirect effects between information anxiety, DHL, and NCC. To assess the model fit, the following criteria were used: χ²/df < 3, comparative fit index (CFI) > 0.9, Tucker–Lewis index (TLI) > 0.90, standardized root mean square residual (SRMR) < 0.08, and root mean square error of approximation (RMSEA) < 0.08 [62]. The statistical significance was set at P < 0.05, with two-tailed testing.
Results
General characteristics of the participants and scores for each scale
A total of 608 registered nurses were included in this study. Table 1 shows the general characteristics of the surveyed nurses. Most nurses were female. The age of the nurses ranged from 20 to 54 years (mean ± SD: 32.06 ± 7.19), and median time of nursing experience was 10 (Q1 5, Q3 13; range 0.7–35 years). Half of the nurses had a bachelor’s degree or above. More than half of the nurses had an average monthly income of more than 5,000 yuan. The mean scores of nurses’ information anxiety, DHL, and NCC were 3.03 ± 0.91, 2.46 ± 0.56, 2.72 ± 0.88, respectively.
The correlation of variables
As shown in Table 2, Pearson’s correlation coefficient showed that there was a negative correlation between the score of information anxiety and NCC (r = -0.200, P < 0.001) and DHL (r = -0.303, P < 0.001). The NCC score (r = 0.333, P < 0.001) was significantly positively correlated with the DHL scores.
Mediating role of DHL on information anxiety and NCC
A path analysis was performed to estimate the direct and indirect impacts of both DHL and information anxiety on NCC among nurses (Fig. 2). NCC was considered as the dependent variable, information anxiety as the independent variable, and DHL as the mediating variable. A structural equation model was constructed based on theoretical framework and previous studies. The findings indicated a good fit between the model and the data (Table 3).
The structural model of this study. Note *P<0.05, *P<0.001; IL information literacy anxiety; IQ information quality anxiety; IT information retrieval tool anxiety; IN information quantity anxiety; IP information processing Anxiety; IA information acquisition anxiety, CC clinical care; LC leadership; IR interpersonal relationship; LP legal/ethical practice; PD professional development; TC teaching-coaching; CR critical thinking/research aptitude. DQ1 operational skills; DQ2 navigation skills; DQ3 information searching; DQ4 determining relevance; DQ5 evaluating reliability; DQ6 adding self-generated context; DQ7 protecting privacy
As shown in Fig. 2, information anxiety could negatively predict DHL (β = −0.297, P < 0.001) and NCC (β = -0.119, P < 0.05), DHL could positively predict NCC (β = 0.306, P < 0.001). Further, DHL partially mediated the relationship between information anxiety and NCC, and the total mediating effect was 0.091, the total effect was 0.209 (Table 4). The results of the Bootstrap mediating effect test showed that the mediation effect accounted for 43.54% of the total effect.
Discussion
This study aimed to determine whether DHL mediates the association between information anxiety and NCC in Chinese registered nurses. First, the findings revealed that information anxiety had an adverse impact on NCC among registered nurses. Second, DHL was positively correlated with NCC. Third, DHL played a mediating role in the association between information anxiety and NCC in registered nurses. Our findings substantiate the hypotheses we posited initially.
Relationship between information anxiety and core competency of nurses
As for the relationship between information anxiety and NCC in registered nurses, the study has identified a correlation between a severe degree of information anxiety and lower NCC. The ability to locate relevant information to guide clinical practice is crucial for high-quality nursing care and patient safety [63]. However, nurses report the following challenges in clinical practice when it comes to addressing clinical issues, especially in locating the most relevant evidence, identifying appropriate sources, adopting effective search methods, and critically evaluating evidence [64]. When mixed messages and information overload occurred, they may have caused confusion and affected the psychological health of nurses [32, 33]. Maharaj et al. [65] believed that poor mental health among nurses could have a negative impact not just on the individual but also on professional performance and, consequently, on the quality of patient care. Relevant studies [66, 67] also showed that feelings like anxiety may have debilitating effects that reduce work output and clinical decision-making ability of nurses, ultimately, leading to debilitating NCC. This result emphasizes that nursing leaders should identify symptoms of anxiety in nurses early and provide customized support and additional services when using digital health technologies.
Relationship between digital health literacy and core competency of nurses
Furthermore, this study found a positive relationship between DHL and NCC, and DHL demonstrated a positive and direct predictive effect on NCC (β = 0.306, P < 0.001). This indicates that higher DHL scores among nurses were correlated with more positive performance in their core competencies. NCC is the key to ensuring the provision of high-quality nursing care [68]. This competency encompasses a range of attributes, including knowledge, skills, talents, and personal characteristics, which collectively empower nurses to execute tasks effectively [12]. As society and the healthcare environment continue to change and digital technologies increasingly affect nursing practice, the evolving nature of NCC becomes apparent. The growing demand underscores the importance of capacity building and ongoing professional development [12, 69]. Study [70] has shown that high DHL was pivotal for nurses to adapt to the digital transformation of healthcare. Nurses with better skills and knowledge necessary to use online health resources would be more actively engaged in overall health-promoting behaviors and self-improvement [71]. Previous study [46] found that individuals with high DHL levels were generally better at solving health problems and promoting healthy behaviors compared to those with low DHL levels. This means that nursing staff with higher DHL levels tend to exhibit better nursing performance and capabilities.
The mediating role of digital health literacy in the relationship between information anxiety and core competency of nurses
This study revealed that the partially mediating role of DHL in the association between information anxiety and NCC. This means that when nurses are overwhelmed by information and accompanying anxiety, which compromises NCC, nevertheless, augmenting nurses’ DHL mitigates this impact. This finding is consistent with Tell [53], which holds that DHL mediates the relationship between the effect of noise on digital health contextual factors and the extent to which an end user is informed and empowered [53]. In other terms, greater DHL negates the adverse effects of noise triggered by digital health contextual factors and promotes a positive digital health experience [53]. The digital transformation in the healthcare industry has also increased the demand for enhancing the digital capabilities of current and future healthcare professionals [72]. For nurses, mastering the skills of identifying and processing information in stressful and demanding clinical work is a significant challenge [73]. The vast amount of information could potentially lead to information overload for them, which in turn might make them feel overwhelmed and anxious, there was considerable concern that such circumstances had the potential to impact nurses’ nursing practice abilities [31, 74]. However, nurses with advanced DHL can efficiently obtain, identify, and utilize internet resources to address practical clinical challenges [46, 47]. Our findings are consistent with a previous study [75], which revealed that higher DHL was associated with greater information satisfaction, leading to reduced anxiety levels. It’s worth noting that this study was conducted with student population. DHL will be indispensable for both healthcare providers and patients, playing a crucial role in enhancing the quality of nursing and patient outcomes [76]. Therefore, nursing managers should prioritize identifying and mitigating information anxiety in nursing practice, alongside devising long-term educational strategies and initiatives geared towards bolstering nurses’ DHL. Nurses are encouraged to harness internet resources fully, engage in active search, discovery, comprehension, and pursue evidence-based solutions for complex nursing issues. This proactive approach aims to strengthen the application of critical thinking and core competencies [75], enabling the delivery of superior nursing services to patients.
Limitations
Several limitations are included in this study. First, the evaluation of NCC is currently based on self-reported, which may produce bias. Future research could explore alternative methods such as peer evaluation or performance indicators for a more objective assessment. Second, the recruitment of nurses from only three tertiary hospitals located in a single province, restricts the applicability of the study’s results to other regions and populations. To enhance comprehension of the correlation between information anxiety, DHL, and NCC among nurses, it is advisable to expand the sample size and ascertain variations across regional scales.
Conclusions
We found that information anxiety negatively impacted the NCC, and DHL partially mediated this relationship in this cross-sectional study. DHL, as a critical asset in the digital health workplace, mitigates the effects of information anxiety on NCC in the digital era. In response to the digital transformation of the health sector, nurses have expanded their scope of activity through this innovative process. Therefore, nursing managers should strengthen the evaluation of nurses’ DHL and devise effective support strategies to enhance DHL, thus improving the NCC.
Data availability
The datasets analysed during the current study are available from the corresponding author on reasonable request.
Abbreviations
- CR-DHLI:
-
Chinese revision version of the Digital Health Literacy Instrument
- IAS:
-
Information Anxiety Scale
- CIRN:
-
Competency Inventory for Registered Nurses
- ICTs:
-
Information and communication technologies
- NCC:
-
Nurses’ core competency
- DHL:
-
Digital health literacy
- TMeHL:
-
Transactional Model of eHealth Literacy
- SEM:
-
Structural equation modeling
- SD:
-
Standard deviations
- IQR:
-
Interquartile range
- ML:
-
Maximum likelihood
- CI:
-
Confidence interval
- CFI:
-
Comparative fit index
- TLI:
-
Tucker–Lewis index
- SRMR:
-
Standardized root mean square residual
- RMSEA:
-
Root mean square error of approximation
References
The emerging field of mobile health | Science Translational Medicine. [cited 2023 Oct 2]; https://www.science.org/doi/https://doi.org/10.1126/scitranslmed.aaa3487
Information. and Communication Technologies (ICT) | AIMS [Internet]. [cited 2024 Jul 18]. https://aims.fao.org/information-and-communication-technologies-ict
Nursing and information and communication technology (ICT). A discussion of trends and future directions. Int J Nurs Stud. 2011;48(10):1302–10.
Rouleau G, Gagnon MP, Côté J, Payne-Gagnon J, Hudson E, Dubois CA. Impact of Information and Communication Technologies on nursing care: results of an overview of systematic reviews. J Med Internet Res. 2017;19(4):e6686.
Cermak CA, Read H, Jeffs L. Health Care professionals’ experiences with using information and Communication technologies in Patient Care during the COVID-19 pandemic: qualitative study. JMIR Form Res. 2024;8:e53056.
Cherrez-Ojeda I, Robles-Velasco K, Osorio MF, Ormaza Vera A, Sarfraz Z, Sarfraz A et al. A systematic review and Meta-analysis of Mobile Health Applications and Telemonitoring in atopic Dermatitis Self-Management. Dermatol Ther (Heidelb). 2024.
Varela-Moreno E, Anarte-Ortiz MT, Jodar-Sanchez F, Garcia-Palacios A, Monreal-Bartolomé A, Gili M, et al. Economic evaluation of a web application implemented in primary care for the treatment of Depression in patients with type 2 diabetes Mellitus: Multicenter Randomized Controlled Trial. JMIR Mhealth Uhealth. 2024;12:e55483.
Huter K, Krick T, Domhoff D, Seibert K, Wolf-Ostermann K, Rothgang H. Effectiveness of Digital Technologies to support nursing care: results of a scoping review. J Multidiscip Healthc. 2020;13:1905–26.
Wynn M, Garwood-Cross L, Vasilica C, Griffiths M, Heaslip V, Phillips N. Digitizing nursing: A theoretical and holistic exploration to understand the adoption and use of digital technologies by nurses. [cited 2024 Jul 20]; https://onlinelibrary.wiley.com/doi/https://doi.org/10.1111/jan.15810
Liu M, Yin L, Ma E, Lo S, Zeng L. Competency inventory for registered nurses in Macao: instrument validation. J Adv Nurs. 2009;65(4):893–900.
Meretoja R, Leino-Kilpi H, Kaira AM. Comparison of nurse competence in different hospital work environments. J Nurs Manag. 2004;12(5):329–36.
Chen M, Wang A, Zhou B. Exploring the core competencies of clinical nurses in Chinese tertiary hospitals: a qualitative content analysis. BMC Nurs. 2023;22(1):166.
Liu M, Kunaiktikul W, Senaratana W, Tonmukayakul O, Eriksen L. Development of competency inventory for registered nurses in the people’s Republic of China: scale development. Int J Nurs Stud. 2007;44(5):805–13.
World Health Organization. Global strategy on Digital Health 2020–2024. World Health Organization; 2019.
Jayousi S, Barchielli C, Alaimo M, Caputo S, Paffetti M, Zoppi P, et al. ICT in nursing and Patient Healthcare Management: scoping Review and Case studies. Sensors. 2024;24(10):3129.
Morris-Docker SB, Tod A, Harrison JM, Wolstenholme D, Black R. Nurses’ use of the internet in clinical ward settings. J Adv Nurs. 2004;48(2):157–66.
Lacey EA. Research utilization in nursing practice–a pilot study. J Adv Nurs. 1994;19(5):987–95.
Lewis KO, Popov V, Fatima SS. From static web to metaverse: reinventing medical education in the post-pandemic era. Ann Med 56(1):2305694.
Fujino Y, Kawamoto R. Effect of information and communication technology on nursing performance. CIN: Computers Inf Nurs. 2013;31(5):244.
Wu C, He C, Yan J, Du J, He S, Ji Z, et al. Patterns of information literacy and their predictors among emergency department nurses: a latent profile analysis based on the person-context interaction theory. BMC Nurs. 2024;23:71.
Kaihlanen AM, Gluschkoff K, Laukka E, Heponiemi T. The information system stress, informatics competence and well-being of newly graduated and experienced nurses: a cross-sectional study. BMC Health Serv Res. 2021;21:1096.
Klerings I, Weinhandl AS, Thaler KJ. Information overload in healthcare: too much of a good thing? Zeitschrift für Evidenz, Fortbildung Und Qualität Im Gesundheitswesen. 2015;109(4):285–90.
Guo N, Zhao SZ, Weng X, Wu Y, Luk TT, Wong JYH, et al. Associations of COVID-19 online information sources and information overload with psychological distress symptoms: a population-based study. Transl Behav Med. 2021;11(7):1330–8.
Wurman RS. Information anxiety. First Edition. New York: Doubleday; 1989. p. 356.
Dawes M, Sampson U. Knowledge management in clinical practice: a systematic review of information seeking behavior in physicians. Int J Med Informatics. 2003;71(1):9–15.
Kostoagilas PA, Martzoukou K, George I, Niakas D. In. How nurses behave online? Nurses’ online information needs and internet seeking behaviour. 2014.
Roetzel PG. Information overload in the information age: a review of the literature from business administration, business psychology, and related disciplines with a bibliometric approach and framework development. Bus Res. 2019;12(2):479–522.
Furlow B. Information overload and unsustainable workloads in the era of electronic health records. Lancet Respiratory Med. 2020;8(3):243–4.
Nie JX, Heidebrecht C, Zettler A, Pearce J, Cunha R, Quan S, et al. The Perceived ease of Use and Perceived usefulness of a web-based interprofessional communication and collaboration platform in the hospital setting: interview study with Health Care Providers. JMIR Hum Factors. 2023;10:e39051.
Song C, Nakayama M. Implementation of a patient Summary web application according to the International Patient Summary and Validation in common use cases in Japan. J Med Syst. 2023;47(1):100.
Fernandez R, Green H, Hobbs C, Loveday C, Almasi E, Middleton R, et al. Adaption of the Cancer Information overload scale for pandemics and assessment of infodemic levels among nurses and midwives. Int J Nurs Pract. 2023;29(1):e13055.
Halcomb E, Williams A, Ashley C, McInnes S, Stephen C, Calma K, et al. The support needs of Australian primary health care nurses during the COVID-19 pandemic. J Nurs Manag. 2020;28(7):1553–60.
Ahmed ST. Managing News overload (MNO): the COVID-19 Infodemic. Information. 2020;11(8):375.
Poonia SK, Rajasekaran K. Information overload: a method to share updates among Frontline Staff during the COVID-19 pandemic. Otolaryngology–Head Neck Surg. 2020;163(1):60–2.
Bigdeli S. Affective learning: the anxiety construct in adult learners. Procedia - Social Behav Sci. 2010;9:674–8.
Sa L, Mc J, Aa M, Ja G. Incremental validity of coronaphobia: Coronavirus anxiety explains depression, generalized anxiety, and death anxiety. Journal of anxiety disorders [Internet]. 2020 Aug [cited 2024 Apr 3];74. https://pubmed.ncbi.nlm.nih.gov/32650221/
Arnold M, Goldschmitt M, Rigotti T. Dealing with information overload: a comprehensive review. Front Psychol. 2023;14:1122200.
Mo Y, Deng L, Zhang L, Lang Q, Liao C, Wang N, et al. Work stress among Chinese nurses to support Wuhan in fighting against COVID-19 epidemic. J Nurs Manag. 2020;28(5):1002–9.
Labrague LJ, De los Santos JAA. COVID-19 anxiety among front‐line nurses: predictive role of organisational support, personal resilience and social support. J Nurs Manag. 2020;28(7):1653–61.
Majid S, Foo S, Luyt B, Zhang X, Theng YL, Chang YK, et al. Adopting evidence-based practice in clinical decision making: nurses’ perceptions, knowledge, and barriers. J Med Libr Assoc. 2011;99(3):229–36.
Tran HTT, Nguyen MH, Pham TTM, Kim GB, Nguyen HT, Nguyen NM, et al. Predictors of eHealth literacy and its associations with preventive behaviors, fear of COVID-19, anxiety, and Depression among undergraduate nursing students: a cross-sectional survey. Int J Environ Res Public Health. 2022;19(7):3766.
Infodemic [Internet]. [cited 2024 Apr 25]. https://www.who.int/health-topics/infodemic
Yang K, Hu Y, Qi H. Digital Health Literacy: bibliometric analysis. J Med Internet Res. 2022;24(7):e35816.
van der Vaart R, Drossaert C. Development of the Digital Health Literacy Instrument: measuring a Broad Spectrum of Health 1.0 and Health 2.0 skills. J Med Internet Res. 2017;19(1):e27.
Jeon J, Kim S. The mediating effects of digital literacy and self-efficacy on the relationship between learning attitudes and Ehealth literacy in nursing students: a cross-sectional study. Nurse Educ Today. 2022;113:105378.
Yuan N, Lv ZH, Wen YY, Sun CR, Tao TY, Qian D. The relationship between eHealth literacy and palliative care knowledge, attitudes, and practice among nurses: a cross-sectional study. BMC Nurs. 2023;22:76.
Gartrell K, Han K, Trinkoff A, Cho H. Three-factor structure of the eHealth Literacy Scale and its relationship with nurses’ health-promoting behaviours and performance quality. J Adv Nurs. 2020;76(10):2522–30.
Stellefson M, Hanik B, Chaney B, Chaney D, Tennant B, Chavarria EA. eHealth Literacy among College students: a systematic review with implications for eHealth Education. J Med Internet Res. 2011;13(4):e102.
Machleid F, Kaczmarczyk R, Johann D, Balčiūnas J, Atienza-Carbonell B, von Maltzahn F, et al. Perceptions of Digital Health Education among European Medical students: mixed methods Survey. J Med Internet Res. 2020;22(8):e19827.
Kim K, Lustria MLA, Burke D. Predictors of cancer information overload: findings from a national survey.
Ying W, Cheng C. Public emotional and coping responses to the COVID-19 Infodemic: a review and recommendations. Front Psychiatry. 2021;12:755938.
Kim HK, Tandoc EC. Consequences of Online Misinformation on COVID-19: two potential pathways and disparity by eHealth literacy. Front Psychol. 2022;13:783909.
Paige SR, Stellefson M, Krieger JL, Anderson-Lewis C, Cheong J, Stopka C. Proposing a transactional model of eHealth literacy: Concept Analysis. J Med Internet Res. 2018;20(10):e10175.
Shah R, Goldstein SM. Use of structural equation modeling in operations management research: looking back and forward. J Oper Manag. 2006;24(2):148–69.
Fritz MS, MacKinnon DP. Required sample size to detect the mediated effect. Psychol Sci. 2007;18(3):233–9.
Zhang S, Wang W, Wu S, Ye H, Dong L, Wang J, et al. Analysis of the mediating effect between ehealth literacy and health self-management of undergraduate nursing students’ mental health literacy. BMC Nurs. 2024;23(1):1–8.
Qin L, Li J, Li C. Servant leadership behaviour of head nurse assessment and its linkage with nurse work engagement in China. J Adv Nurs. 2023;79(11):4356–64.
Zhao B, Xu Q, Wang X, Huang L, Zhang Y, Hu R. The sinicization of the Digital Health Literacy Instrument and the test of its reliability and validity. Chin J Nurs Educ. 2024;21(1):89–95.
Shen Y, Lu Q, Cao G, Chen J. Research on user information anxiety in the process of academic information searching. Inform Sci. 2021;39(6):143–51.
Ghasemi E, Master degree in nursing, Nursing and Midwifery Care Research Center, Tehran University of Medical Sciences, Tehran, Iran, Janani L, PhD candidate in Biostatistics, Dept. of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran, Dehghan, Nayeri N, Professor et al. Nursing and Midwifery Care Research Center, Tehran University of Medical Sciences, Tehran, Iran,. Psychometric Properties of Persian Version of the Competency Inventory for Registered Nurse (CIRN). IJN. 2014;27(87):1–13.
Zhang Z, Zhang X, Fei Y, Zong X, Wang H, Xu C, et al. Emotional intelligence as a mediator between spiritual care-giving competency and core competencies in Chinese nursing interns: a cross-sectional study. Support Care Cancer. 2023;31(6):367.
Wang J, Wang X. Structural equation modeling: applications using Mplus. 3rd ed. Wiley Publishing; 2012. p. 478.
Wahoush O, Banfield L. Information literacy during entry to practice: information-seeking behaviors in student nurses and recent nurse graduates. Nurse Educ Today. 2014;34(2):208–13.
Farokhzadian J, Jouparinejad S, Fatehi F, Falahati-Marvast F. Improving nurses’ readiness for evidence-based practice in critical care units: results of an information literacy training program. BMC Nurs. 2021;20:79.
Maharaj S, Lees T, Lal S. Prevalence and risk factors of Depression, anxiety, and stress in a cohort of Australian nurses. Int J Environ Res Public Health. 2018;16(1):61.
Pignatiello GA, Martin RJ, Hickman RL. Decision fatigue: a conceptual analysis. J Health Psychol. 2020;25(1):123–35.
Donovan O, Doody R, Lyons O. The effect of stress on health and its implications for nursing. Br J Nurs. 2013;22(16):969–73.
Cutugno C. Adult-gerontology clinical nurse specialists: the time is now. Geriatr Nurs. 2015;36(3):232–3.
Booth RG, Strudwick G, McBride S, O’Connor S, López ALS. How the nursing profession should adapt for a digital future. BMJ. 2021;373:n1190.
Nazeha N, Pavagadhi D, Kyaw BM, Car J, Jimenez G, Tudor Car L. A digitally competent health workforce: scoping review of Educational Frameworks. J Med Internet Res. 2020;22(11):e22706.
Cho H, Han K, Park BK. Associations of eHealth literacy with health-promoting behaviours among hospital nurses: a descriptive cross-sectional study. J Adv Nurs. 2018;74(7):1618–27.
Mantas J, Ammenwerth E, Demiris G, Hasman A, Haux R, Hersh W, et al. Recommendations of the International Medical Informatics Association (IMIA) on Education in Biomedical and Health Informatics. Methods Inf Med. 2010;49(02):105–20.
Wu C, Zhang L, yuan, Zhang X, yan, Du Y ling, He S, zhe, Yu L, rong et al. Factors influencing career success of clinical nurses in northwestern China based on Kaleidoscope Career Model: Structural equation model. Journal of Nursing Management. 2022;30(2):428–38.
Collins R. Clinician Cognitive overload and its implications for nurse leaders. Nurse Lead. 2020;18(1):44–7.
Chen SC, Huy LD, Lin CY, Lai CF, Nguyen NTH, Hoang NY, et al. Association of Digital Health Literacy with future anxiety as mediated by information satisfaction and fear of COVID-19: a pathway analysis among Taiwanese students. Int J Environ Res Public Health. 2022;19(23):15617.
Alipour J, Payandeh A. Assessing the level of digital health literacy among healthcare workers of teaching hospitals in the southeast of Iran. Inf Med Unlocked. 2022;29:100868.
Acknowledgements
The authors would like to extend their sincere gratitude to the nurses who took part in this research endeavor, in addition to recognizing the invaluable support provided by the nurse administrators of hospitals and healthcare facilities during the research.
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Zhao contributed to analysis and interpretation of the data and writing of the original draft manuscript. Chen assisted in the distribution and collection of questionnaires and the compilation and analysis of data. Yan participated in interpretation of the results and provided critical review of the paper. Lin and Li supervised the project and contributed to the design of the study, the revision, and the review of the final.
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This study was approved by Ethical Committee of Fujian Medical University (2023/107). Prior to data collection, the researcher explained the purpose and procedures of the study to the participants, including that confidentiality was assured and participation in the study was voluntary. Obtained informed consent from all participants, the eligible nurses had the right to withdraw from the study at any time. The information gathered was kept confidential.
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Zhao, BY., Chen, MR., Lin, R. et al. Influence of information anxiety on core competency of registered nurses: mediating effect of digital health literacy. BMC Nurs 23, 626 (2024). https://doi.org/10.1186/s12912-024-02275-3
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DOI: https://doi.org/10.1186/s12912-024-02275-3