1、Introduction

With the widespread application of information and communication technologies in the medical field, telehealth has developed rapidly as a new form of medical care. Telehealth refers to the use of electronic information and telecommunications technologies to support and promote long-distance clinical health care, patient and professional health related education, public health and health administration (Association, 2020). The American Nurses Association has formulated thirteen core principles related to connected health to provide guidelines for health care professionals who use connected health technologies to provide quality care (Association, 2019). In 2018, the National Organization of Nurse Practitioner Faculties (NONPF) recommended incorporating telehealth modalities in nurse practitioner education (Quinlin et al., 2020). In 2019, the National Health Commission of the People’s Republic of China formally issued the "Internet + Nursing Service" Pilot Work Plan to support medical institutions in pilot cities that provide nursing services based on information and communication technology (ICT) (Authority, 2019). Since then, the National Health Commission of the People’s Republic of China has successively issued policies to encourage medical institutions to actively develop the "Internet + Nursing Services" program and support qualified nurses in multi-site practices.

The American Nurses Association divides telehealth into three types:live (synchronous) videoconferencing, remote patient monitoring and mobile health (Association, 2020). These three types, which are widely used in hospitals, nursing homes, communities and homes, have achieved remarkable results in providing medical care services for people with cancer, chronic diseases, infectious diseases, disabilities and frailty. Galiano-Castillo et al. (Galiano-Castillo et al., 2016) provided an eight-week telerehabilitation customized exercise program for patients who had completed adjuvant therapy for stage I to IIIA breast cancer. The results showed that the global health status, physical, role, cognitive functioning, arm symptoms and pain degree. were significantly improved (P < 0.01). Gokalp et al. (Gokalp et al., 2018) provided clinical sensors to measure vital signs for patients with chronic obstructive pulmonary disease or congestive heart failure (CHF). In this study, one passive infrared motion sensor and/or a chair/bed sensor was installed in the patient’s home to obtain their activity data. All data were automatically transmitted wirelessly to the remote server and the ward smart screen, such that abnormal data alarmed clinicians who monitored each patient. This has had a positive impact on the well-being of the elderly by enabling timely intervention. In addition, telehealth has offered a wide range of prevention and treatment health services using information and telecommunication technologies during the outbreak of COVID-19 worldwide. The advantages of telehealth services across time and space effectively reduce the chances of crowd contact and virus transmission, while increasing the service capacity of medical staff (Scott et al., 2020). Kronenfeld et al. (Kronenfeld and Penedo, 2020) noted that ICT provides a convenient channel for disease surveillance of chronic diseases and malignant tumor patients and telehealth services played a key role in preventing adverse disease progression during the COVID-19 crisis.

Telehealth essentially refers to the personalized and targeted services provided to patients by practitioners (doctors, nurses, pharmacists, rehabilitation practitioners, etc.) with the help of information platforms such as mobile phone software and computer systems. The American College of Obstetricians and Gynecologists (ACOG) committee noted that the successful implementation of telehealth requires policy and regulations permission, complete hardware resources of hospitals and sufficient human resources reserves of medical and nursing personnel. It also must ensure that service providers have the necessary hardware, software and reliable, secure internet connections to ensure quality care and patient safety (Anon, 2020). At present, the number of telehealth services led by nurses has gradually increased and it is considered to be an accessible, affordable and valuable health care service (Moreno and Peck, 2020). Whitmore et al. (2020) also proposed that nurse-led digital health interventions provide an innovative way to support and manage patients with chronic diseases and reduce the burden of disease. However, nurses’ skills and attitudes play a key role in the successful implementation of telehealth (Koivunen and Saranto, 2018). Therefore, it is necessary to comprehensively evaluate the preparation of nurses for telehealth and develop training plans to ensure the successful implementation of telehealth. At present, as China’s telehealth model is only in the preliminary stage of development, its registered nurses’ readiness for telehealth must be assessed and discussed.

Telehealth readiness refers to the degree to which users, health organizations and health care systems are prepared to participate in and successfully implement the applications (Jennett et al., 2003a). Yusif et al. (2017) summarize and separate telehealth readiness into technological readiness, core/need/motivational readiness, acceptance and use readiness, organizational readiness, IT skills/training/learning readiness, engagement readiness and societal readiness. Based on this readiness model, Jennett et al. (2003b), (2003c) identified six themes related to readiness, namely, core readiness, structural readiness, income forecast, risk assessment, awareness and education and intragroup and intergroup dynamics through interviews. Based on these themes, they created the Telehealth Readiness Assessment Tool, which includes core readiness, engagement readiness and structural readiness. Legare et al. (2010) reviewed the existing telehealth readiness assessment tool and found that it has a wide range of applications and is strong promoted as it effectively evaluates the factors that affect practitioners’ acceptance of telehealth. However, no research has been conducted that relates to the telehealth readiness of clinical nurses at Chinese hospitals.

Therefore, this study selected clinically registered nurses as the research object, used the TRAT as the evaluation tool to investigate the current situation of telehealth readiness and analyse its influencing factors to provide a reference for building telehealth service platforms and telehealth education courses and promoting the successful implementation of telehealth.

2、Methods

A cross-sectional survey with multicentre design was conducted to collect data from clinical nurses in China.

2.1. Participants

Using convenience sampling, 3386 registered nurses were recruited between October and December 2020 from nineteen Chinese clinical hospitals, including three primary hospitals, six secondary hospitals and ten tertiary hospitals. To be eligible, participants had to have passed the Chinese Nurses Practice Examination and completed registration, be currently practising as a clinical nurse and be willing to participate in this study. Those nurses who were in clinical nursing management, teaching or scientific research positions or who were absent for more than one week due to maternity issues, sickness, accidents, etc. were excluded from participating. According to the Hospital Classification Management Standards, first-level hospitals are primary health care institutions, secondary hospitals are regional technology centers for medical prevention and tertiary hospitals are medical prevention technology centers with comprehensive medical treatment, teaching and scientific research capabilities. Clinical nurses were recruited according to the level of hospital to ensure representativeness of the participants.

2.2. Measures

2.2.1. Demographic and telehealth practice-related variables

The demographic variables included age, gender, education level, working department, working years, professional title, position, prepa ration category, marital status, monthly income and hospital level. Additionally, we developed a simple questionnaire to investigate nurses’ cognition, willingness to participate in and experience with telehealth service by asking the following questions: “Do you know the telehealth service model?” “Have you ever applied telehealth platforms (such as telephone consultation, video conferencing, health management apps, etc.) to provide services for patients?” “Are you willing to provide telehealth services for patients using information technology?” We also collected information about nurses’ views of policy awareness and manpower allocation on a 2-point Likert-type scale ranging from negative to positive by asking the following items: “Do you understand the telehealth policies promulgated by the state?” “Do you think the department nurse configuration is sufficient?”.

2.2.2. Telehealth readiness assessment tools (TART)

Our research group developed a Chinese version of TRAT(Zhen et al.,2020). With the authorization of Dr. Jennett, the author of the source scale, TART was translated, retranslated and revised based on the Brislin translation model (Jones et al., 2001):

(i) Translation: Two Chinese-speaking and English-knowledgeable translators independently translated all the items and options of the source English scale to create the Chinese first drafts Z1 and Z2.

(ⅱ) Synthesis: A nursing education expert with a doctorate compared and reconciled the two versions one-by-one and organized team members to participate in the discussion to form a reconciled version of the Z3 scale.

(ⅲ) Retranslation: Two bilingual translators who did not have access to or use the source scale were selected to complete the retranslation independently to form the English versions of Z3–1 and Z3–2. One of the translators is a master of translation through professional English level eight and translation level two and the second is an English major graduate tutor. Team members were invited to discuss the English version and revise it to form the final English version. The source author was invited to review the English version of the retranslated scale.

(ⅳ) Expert consultation: The research team invited five experts to consult and assess the expression method and content of the scale, integrated expert opinions and adjusted the scale to make it more suitable for the Chinese cultural background. Three items were modified. For example, Item 1, “I have a feeling of dissatisfaction with the current available ways of delivering care, e.g., status quo” was adjusted to read, “I am not satisfied with the existing care services”. Item 8, “I have examples and evidence of telehealth applications in similar contexts/environments/communities” was adjusted to read, “I can list the application cases and evidence of telehealth models in the community/ family”. and Item 13, “I have telehealth reimbursement plans in place” was adjusted to read “I think telehealth services can be included in medical insurance”.

(ⅴ) Pre-investigation: Thirty clinical nurses were recruited by convenience sampling method for pre-investigation and cognitive in terviews to evaluate the concept, semantics and content of the scale. There were no special modifications, and the scale completion time was generally five to ten minutes.

A total of 110 medical personnel were enrolled to voluntarily complete the questionnaire for the purpose of conducting exploratory factor analysis and calculating Cronbach’s coefficient. Three common factors of the Chinese version TRAT were extracted, and the cumulative contribution rate of variance reached 61.858%. Each item entered the scope of its own dimension except Item 17, which may be due to the research object and cultural differences. Combined with the current implementation status of telehealth in China, it was decided to retain Item 17 as part of the core readiness dimension. The load of each item on the corresponding common factor was greater than 0.4 and greater than the load value on other factors, thus achieving the equivalence of scale structure and theory.

The scale included three dimensions of core/engagement/structural readiness and adopted a 5-point Likert-type scoring method. The correlation coefficient between each item and the total score was 0.408–0.680. The content validity analysis indicates that the CVI of each item was 0.88–1.00 and the average CVI was 0.93. Internal consistency was acceptable for core readiness (four items, Cronbach’s α = 0.743, range 4–20 points), engagement readiness (seven items, α = 0.878, range 7–35 points), structural readiness (six items, α = 0.866, range 6–30 points) and total scale (17 items, α = 0.861, range 17–85 points). The global score is interpreted at three levels of readiness, that is, high level: above 80, indicating that practitioners can well use telehealth; moderate level: between 61 and 80, indicating that practitioners face certain factors may adversely affect the use of telehealth; and low level: below 61, indicating that there are barriers to the successful use of telehealth by practitioners.

2.3. Data collection

Clinical nurses completed the online questionnaire through Questionnaire Star, which is a free questionnaire platform. The nursing directors in the hospitals were then contacted and sent the electronic questionnaire links to the nurses’ WeChat communication group. The objectives of the survey, inclusion criteria of participants and submission deadline were explained to the nurses by the head nurse of their departments. If the eligible nurses agreed to participate in the survey, they were asked to respond to the questions according to the instructions in the questionnaire. The head nurses reminded the nurses to respond before the submission deadline. To ensure the validity of the questionnaire and prevent the phenomenon of missing questions, each question was set to the mandatory answer and the answer reminder was set. We also set the Internet Protocol (IP) address filling limit, that is, one IP address can only be filled in once to avoid nurses from filling in the questionnaire repeatedly. Before the formal survey, the researchers who were familiar with the research topic read and completed the questionnaire and determined that the minimum completion was 60 s. The link to the survey was clicked 3409 times, of which 23 were excluded because the answer times were less than 60 s. The final dataset consisted of 3386 questionnaires (completion rate: 99.3%).

2.4. Ethical considerations

The study was approved by the Life Science Ethics Review Committee of Zhengzhou University (ZZUIRB2020–66) and conducted in accordance with the principles of the Declaration of Helsinki and established guidelines. The survey was anonymous, voluntary and completely confidential. The nurses were informed that submitting the completed questionnaire was considered implied consent.

2.5. Statistical analysis

We conducted all statistical data analyses using SPSS version 21.0 (SPSS Inc., Chicago, IL, USA). We described categorical data as absolute frequencies and percentages and continuous data as the mean and standard deviation (SD). We reported 95% confidence intervals (95% CIs) of observed percentages to provide population estimates for readiness levels. Additionally, we applied the Kolmogorov–Smirnov test for normality analysis, which revealed that all variables did not obey a normal distribution (P < 0.05). Therefore, we used the Mann–Whitney U test and Kruskal–Wallis H test in a nonparametric test to analyse the influencing factors and then applied the Bonferroni correction method to compare multiple independent samples, with a significance level of 0.05. Furthermore, we used the Spearman two-sided test method to analyse the correlation between nurses’ service willingness, mode cognition, policy guidance, service experience, manpower allocation and telehealth readiness level.

3、Results

3.1. Participants’ characteristics

A total of 3386 nurses (3247 female and 139 male) who met the inclusion criteria were recruited, of which 115 nurses were from pri mary hospitals, 745 nurses were from secondary hospitals and 2526 nurses were from tertiary hospitals. The participants’ demographic characteristics are presented in Table 1.

3.2. The scores of clinical nurses’ telehealth readiness

The average score of clinical nurses’ telehealth readiness was in the category between 61 and 80 points (mean 61.23, SD 11.61), according to which several factors exhibited an unfavorable influence on telehealth use by nurses. The scores of each dimension are shown in Table 2. While 8.1% (95% CI 7.2–9.0%) were in a good position, 42.0% (95% CI40.3–43.6%) of the nurses believed that certain items might adversely affect their use of telehealth, while most (49.9%, 95% CI 48.4–51.8%) perceived barriers (Table 3).

3.3. Influencing factors of clinical nurses’ telehealth readiness

The factor analysis results with statistically significant differences from the SPSS are listed in Table 4. Nurses with service willingness and service experience had higher scores in telehealth readiness (P < 0.001). Nurses who understood the telehealth model and related policies and believed that the manpower allocation of their department was adequate also scored significantly high (P < 0.001). The nonparametric independent sample test was performed on the variables of working position and marital status to allow for pairwise comparisons between groups. The results revealed that there was a significant difference in the score between the nurse and the head of responsible nursing group (P = 0.012, t = 2.521) and married nurse scored significantly lower than unmarried nurse (P = 0.038, t = 2.073).

3.4. Relationship between telehealth practice-related variables and telehealth readiness

Spearman’s correlation analysis indicates that telehealth practice related variables such as service willingness, mode cognition, policy guidance, service experience and manpower allocation are positively correlated with telehealth readiness level and that the difference is statistically significant (Table 5). Additionally, we combined the results of the correlation analysis and referred to the readiness model to construct a mechanism diagram that affects nurses’ telehealth readiness level (Fig. 1). We summarize service willingness, service experience and mode cognition as personal factors and policy guidance and manpower allocation as organizational factors and find that both personal and organizational factors affect.

4、Discussion

In our study, the score of clinical nurses’ telehealth readiness ranged from 61 to 80 points (mean 61.23, SD 11.61), of which 49.9% (95% CI 48.4–51.8%) of the nurses scored at a low level and 42.0% (95% CI 40.3–43.6%) of the nurses scored at a medium level, indicating that there were still some factors that hinder the successful implementation of telehealth services. Prendergast et al. (Prendergast and Honey, 2019) noted that lack of telehealth training and poor operability of equipment were obstacles for nurses with respect to accepting telehealth. At present, global education resources for telehealth are still relatively scarce and most nursing colleges have not included relevant learning plans in their syllabi (Chike-Harris et al., 2021), resulting in a lack of access for nursing students to understand the concepts of telehealth and clinical practice modes. As nursing students have not received adequate telehealth education, there will be a negative effect on their telehealth readiness in their future careers (Gibson et al., 2020). Arends et al. (2021) developed a telehealth course for nurse practitioners based on evidence, including demonstration, operation and simulation of telehealth, which significantly improved the readiness, confidence and ability of nurse practitioners for telehealth. Therefore, nursing educators should construct a complete telehealth education or training system as soon as possible and establish curriculum content and service specifications according to the core principles of telehealth/connected health formulated by the American Nurses Association to improve the telehealth readiness of clinical nurses.

A total of 68.8% (2331) of nurses in this study did not understand the telehealth service model, 59.4% (2010) did not understand the telehealth-related policies issued by the national government and 55.6% (1883) of nurses had not used information technology to provide telehealth services for patients. Moreover, it was concluded that nurses lack the theoretical and practical understanding of the telehealth model, which affects their perception of the usefulness of telehealth and their preparedness for service. Steingass and Maloney-Newton (2020) also proved that nurses must have a detailed understanding of the implementation process and content division of telehealth to ensure that they practice within the scope of policy permission. In addition, the provision of online services based on the information and communication technology has certain security risks, but the legal protection and safety supervision measures for telehealth services in China are still not perfect, nurses in the process of providing telehealth services face huge medical services and personal safety risks (Zhang Yuanyuan and Chunhe, 2019), which to some extent hinders the participation of nurses in the implementation of telehealth services. However, telehealth training and local government support were identified as promoting factors for telehealth implementation (Prendergast and Honey, 2019), thus suggesting that in addition to advocating telehealth education, we should also advocate that government departments formulate risk su pervision and security systems for telehealth services and increase the publicity and promotion of policies to support the implementation of nurse-led telehealth at the two levels of policy guidance and legal protection.

Of the factors studied, the two demographic factors, working position and marital status, exhibited significant differences in the nurses’ telehealth readiness scores. Among the working position factors, the head of the responsible nursing group scored higher than that of the ordinary nurses and the married nurses scored higher than that of the unmarried nurses in terms of marital status (P < 0.05). This could be explained by the fact that the nurses who are the head of the responsible nursing group have rich clinical work experience and higher professional title. The Internet + Nursing Services Pilot Work Plan issued by the National Health Commission of China specifies that only registered nurses with more than five years of clinical nursing work experience and with the title of senior nurse or above can provide telehealth services (Authority, 2019). Therefore, the head of the responsible nursing group has more opportunities to participate in telehealth services and training than ordinary nurses and thus are able to improve personal readiness because of their clinical practice and learning. Hu et al. (Yaojia et al., 2020) also found that nurses with higher working positions paid more attention to the cultivation and development of their abilities and actively gain new knowledge and new ideas to cope with the rapid development of information technology, thereby improving their telehealth ability.

Additionally, in the traditional Chinese cultural environment, married women must work while also caring for their families to reduce the financial burden on the families. Telehealth expands the scope of the practice of nursing and requires additional time and emotional labor, thus economic compensation should be provided for those engaging in telehealth models (Johnson. et al., 2018). Konrad et al. (2017) proved that the telehealth model not only promotes the health of patients but also increases the personal income of nurses and improves their pro fessional ability. This also indirectly increases the willingness of married nurses to participate in telehealth services and increases their access to relevant knowledge, thus enhancing their initiative to successfully implement telehealth, consistent with the results of Li et al. (Jingjian et al., 2020). Our study suggests that clinical nursing managers should develop incentive mechanisms for telehealth services, relax the qualification limits for registered nurses to participate in services and training and encourage nurses to actively participate in telehealth services.

Among the telehealth practice-related variables, the five factors of model cognition, policy guidance, service willingness, service experience and manpower allocation exhibit a significant impact on the telehealth readiness scores. There is a positive correlation between various factors and the telehealth readiness level (P < 0.05). In our study, 91.9% (3112) of the nurses expressed their willingness to apply ICT and provide telehealth services for patients. This could be explained by the prevalence of the novel coronavirus disease (COVID-19), consistent with Mahoney (2020). COVID-19 limits conventional face-to-face care, forcing clinical nurses to quickly adapt to or introduce telehealth technology to provide professional nursing services. In addition, the implementation of telemedicine services by nurses improves nursing performance, promotes the efficiency and quality of nursing work and reduces errors in exchanging and sharing information with others (Hah and Goldin, 2019). In the process of telehealth services, nurses may gradually perceive the usefulness and availability of telehealth, which, to some extent, may stimulate nurses’ willingness and readiness to serve.

The correlation between nurses’ cognition of the telehealth model and policy guidance was the highest (r = 0.620, P < 0.05). The national and provincial health committees of China have also issued some policy documents and work plans for telehealth services, which present a clear exposition on the supply subjects, service objects, service projects, management systems and service specifications, platform management, related responsibilities, risk prevention and control, pricing and payment mechanisms (Medical Administration and Hospital Authority, 2019). It also provides a convenient way for nurses to understand the telehealth model, perceive its benefits and evaluate obstacles to carrying out telehealth. This suggests that nursing educators can formulate service standards and continue education courses combined with telehealth-related policies to guide nurses to participate in and implement telehealth services.

The more adequate the department staffing is, the higher the nurses’ telehealth readiness scores (P < 0.05). However, 32.5% of the nurses in our study believed that the current human resource allocation in the department was insufficient. A collaborative report drafted by the World Health Organization (WHO) in partnership with the International Council of Nurses (ICN) and Nursing Now reveals that there are currently just under 28 million nurses worldwide, leaving a global shortfall of 5.9 million (Chaib et al., 2020). Especially during the outbreak of the COVID-19 epidemic, with the increase in the number of confirmed patients and nurses infected, clinical nurses are shouldering heavy nursing workloads per capita, which results in a lack of nonclinical time to provide telehealth services for discharged patients (Debra et al., 2020). With inadequate time (MacGeorge et al., 2021) and heavy workloads (Eysenbach, 2018) of nurses as key barriers to the implementation of telehealth plans, which limits the participation of nurses in telehealth and is not conducive to improving their telehealth readiness. Our study suggests that nursing educators should increase the education and training of nurses, especially public health nurses, that clinical nursing managers should consider setting up full-time staff for telehealth services in departments and hospital-level telehealth services quality control teams and that telehealth should be gradually integrated into the clinical nursing service path.

5、Limitations

As our study was based on a convenience sample, it may have exhibit selection bias and limit the generalizability of the findings. Therefore, future studies are needed to optimize data collection methods and expand the scope of investigations. In addition, the TART used in our study are based on self-report scales, which could involve recall bias. Finally, it must be noted that we only explored the influence of demographic and telehealth practice-related factors on the telehealth readiness of nurses. There may be other factors that affect the telehealth readiness of clinical nurses and the mechanism model of individual and organizational factors regarding telehealth readiness level should be further improved and verified. Hence, the future studies could consider adopting the semi-structured interviews to explore the influencing factors of nurse-led telehealth implementation and further supplement and validate the model.

6、Conclusion

The Chinese version of the TRAT has good reliability and validity and can be widely used in the investigation of clinical nurses. However, the telehealth readiness of clinical nurses in China needs to be improved and readiness varied according to working position and marital status. We also found that telehealth readiness level is related to personal factors, i.e., demographic factors, mode cognition, service willingness and service experience and to organizational factors, such as policy guidance and manpower allocation. Additionally, the clinical nurses have insufficient awareness of the telehealth model and less use of information technology to provide telehealth services for discharged patients, but they have high willingness to participate in telehealth. Accordingly, nursing educators should construct a sound telehealth education or training system as soon as possible, establish a curriculum content according to the telehealth policy and core principles, improve telehealth service ability and promote the successful implementation of telehealth services for nurses.

Funding information

This research was supported by the National Natural Science Foundation of China (71874162).

CRediT authorship contribution Statement

Tian Yu-tong: Methodology, Data Curation, Formal analysis, Writing - Original Draft. Zhang Yan: Conceptualization, Resources, Writing - Review & Editing. Liu Zhen: Validation. Xu Bing: Investigation. Cheng Qing-yun: Investigation.

Declaration of Competing Interest

The author(s) declare that there are no potential conflicts of interest with respect to the research, authorship and/or publication of this

Acknowledgments

We express our great appreciation to the clinical nurses who participated in this study.

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This article is excerpted from the Nurse Education in Practice 58 (2022) by Wound  World.