This study is a quantitative methodological research conducted to develop and evaluate a measurement tool for assessing digital leadership among clinical nurses. The development of the DLS-CN was carried out in 2 phases, based on the tool development process proposed by DeVellis and Thorpe [24]. In the first phase, preliminary items were developed, followed by content validity testing, cognitive interviews, and a pilot survey. In the second phase, the tool was administered to clinical nurses to examine its reliability and validity.

This study was approved by the Institutional Review Board of Daegu Catholic Medical Center (CR-23-148). The online survey introduction clearly explained the study’s purpose, informed consent, procedures, voluntary participation, confidentiality, potential benefits and risks, and stated that the data would be used only for research purposes. Participants received a small token of appreciation for their involvement. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki.

A total of 446 clinical nurses participated in the survey (Table 1). Among them, 223 participants were included in the EFA, with an average age of 30.71 (SD 5.45) years. Most participants were female (208, 93.3%). Regarding the type of hospital where they worked, 137 participants (61.4%) were employed at tertiary hospitals and 86 (38.6%) at general hospitals. The most common region was Seoul, the capital, with 106 participants (47.5%). The average length of clinical experience was 70.41 (SD 46.68) months. In terms of work departments, 137 participants (61.4%) worked in general wards, 52 (23.3%) in special units (eg, intensive care units, operating rooms, emergency rooms), 17 (7.6%) in outpatient clinics, and 17 (7.6%) in other departments. For the CFA, 223 participants were included, with an average age of 31.07 (SD 4.81) years. The majority were female participants (200, 89.7%). A total of 131 participants (58.7%) worked in tertiary hospitals and 92 (41.3%) in general hospitals. The highest number of participants was also from Seoul (99, 44.4%). The average length of clinical experience was 74.31 (SD 57) months. Regarding work departments, 147 participants (65.9%) worked in general wards, 38 (17.0%) in special units, 25 (11.2%) in outpatient clinics, and 13 (5.8%) in other departments.

To examine the distribution of items in the 223 collected responses for factor analysis, the mean, SD, skewness, and kurtosis were calculated for each item. Since none of the items had an absolute skewness value greater than 3.0 or an absolute kurtosis value greater than 8.0, all items met the assumption of normality [33]. Item-total correlation coefficients were reviewed, and items with coefficients below 0.30 or above 0.80 were removed, as these values suggest low contribution to the scale or item redundancy [34]. Seventeen items were removed due to low internal consistency reliability and weak correlation between item pairs. Based on corrected item-total correlation and changes in reliability after item deletion [33], the corrected item-total correlations ranged from 0.43 to 0.72, and the reliability did not significantly change upon item deletion (Table 2). As a result, 30 items were retained for further analysis.

EFA using principal component analysis with varimax rotation was conducted on the 30 items of the DLS-CN. Prior to the factor analysis, data adequacy was assessed using the KMO measure and the Bartlett test of sphericity. The KMO value was 0.96, indicating excellent sampling adequacy, and the Bartlett test of sphericity was statistically significant [35], confirming the data’s suitability for factor analysis. To determine the number of factors, eigenvalues greater than 1.0 and a cumulative variance explanation rate exceeding 60% were used based on Kaiser rule. Scree plot analysis and the interpretability of the factor structure were also considered. Items were retained based on communalities greater than 0.40, factor loadings above 0.40, and at least 3 items per factor [36]. One item with a factor loading below 0.40 was removed. The final analysis included 29 items, with a KMO of 0.95 and a statistically significant Bartlett test (χ²₈₂₀=4799.3; P<.001), indicating the appropriateness of factor analysis. The EFA extracted 4 factors with eigenvalues greater than 1.0, explaining a cumulative variance of 56.9%. Communality values ranged from 0.52 to 0.64, and all factor loadings exceeded 0.40, indicating good model fit. The purpose of factor analysis is to understand the pattern of data and clarify the interpretability of factors [37]. The factor loadings and item contents were examined to ensure conceptual coherence. Cross-loading items that were theoretically essential were assigned to conceptually valid factors. The inter-item correlation coefficients within subfactors were as follows: factor 1: 0.43 to 0.64; factor 2: 0.35 to 0.57; factor 3: 0.35 to 0.51; and factor 4: 0.39 to 0.052, indicating that the model estimation was appropriate (Table 3).

CFA was conducted to verify whether the 4 factors and 29 items extracted during the EFA appropriately reflected the constructs of digital leadership among clinical nurses. The model’s goodness-of-fit was assessed to confirm the adequacy of the structure. To evaluate the model fit, the chi-square statistic was examined. A model was considered acceptable if the normed chi-square χ²/df was less than 3, the comparative fit index was above 0.90, the root mean square error of approximation was below 0.06, and the standardized root mean squared residual was below 0.80 [38]. The results of the CFA indicated that the chi-square value was statistically significant, and the normed chi-square χ²/df was 1.8, satisfying the criterion of being below 3. The comparative fit index was 0.91, exceeding the threshold of 0.90. The root mean square error of approximation was 0.06, which meets the criterion for a good model fit. The standardized root mean squared residual was 0.05, which is below the acceptable cutoff of 0.08, indicating that the model had a generally good fit (Table 2).

To verify the convergent validity of each factor, the standardized factor loading was required to be 0.5 or higher, the significance of the unstandardized regression coefficient (critical ratio) was required to exceed 1.97 (P<.05), the construct reliability had to be 0.7 or higher, and the average variance extracted (AVE) needed to be 0.5 or higher [39]. The results of the convergent validity test showed that the critical ratio values of the unstandardized regression coefficients ranged from 7.83 to 10.63, significantly exceeding the threshold [30], confirming that the measured items met the conditions necessary for validity testing. The standardized factor loadings for all factors met the criterion of 0.5 or higher. The AVE values for each factor ranged from 0.52 to 0.57, satisfying the minimum requirement of 0.50. The construct reliability values ranged from 0.85 to 0.90, all exceeding the minimum requirement of 0.70. Therefore, the DLS-CN demonstrated adequate convergent validity in terms of item construction. Through this, it was confirmed that 4 factors consistently measured the construct of “Digital Leadership Scale for Clinical Nurses,” and that the 29 items consistently represented the corresponding factors. To assess discriminant validity, interconstruct correlation matrices were examined (Table 4). Discriminant validity was evaluated by checking whether the AVE of each factor was greater than the squared correlation coefficients between the factors [39]. In some cases, such as the ability to use digital technology–digital collaboration mindset, ability to use digital technology–organizational influence, digital safety management–digital collaboration mindset, and digital collaboration mindset–organizational influence, the squared correlations between factors exceeded the AVE of the individual constructs, indicating that discriminant validity was only partially satisfied.

To verify convergent validity, the correlations with the Nursing Informatics Competency Measurement Tool [31] and the Self-Leadership Scale [32] were examined. The correlation with the Nursing Informatics Competency Scale was 0.82 (P<.001), and the correlation with the Self-Leadership Scale was 0.83 (P<.001). Since the correlation coefficients were all above 0.70, convergent validity was confirmed.

Reliability was tested using Cronbach α, with a criterion of 0.70 or higher [29,40]. Cronbach α for the 29 items measuring DLS-CN was 0.95.

By subfactor, Cronbach α was as follows: factor 1 (ability to use digital technology): 0.88; factor 2 (digital safety management): 0.78; factor 3 (digital collaboration mindset): 0.86; and factor 4 (organizational influence): 0.87.

Since Cronbach α for all subfactors and the overall tool exceeded 0.70, reliability was confirmed.

In this study, the final version of the DLS-CN consisted of 29 items across 4 factors (Table 5).

By subfactor, the items were as follows: 8 items for the ability to use digital technology, 5 items for digital safety management, 8 items for a digital collaboration mindset, and 8 items for organizational influence.

This study was conducted to develop a tool to measure digital leadership among clinical nurses, based on the instrument development steps proposed by DeVellis and Thorpe [24]. The research was carried out in 2 phases: the development of preliminary items and the evaluation of the instrument’s validity and reliability.

During the item development phase, a conceptual framework was established by integrating the components of digital leadership identified in previous concept analyses and literature reviews on digital leadership in clinical nursing. Preliminary items were selected from the initial items through a content validity assessment by experts, followed by cognitive interviews and a pilot survey, which were used to derive the final set of preliminary items. Throughout this process, expert feedback and identified issues were systematically reviewed and refined.

In the instrument evaluation phase, data were collected from 446 clinical nurses through an online survey. A random sample of 223 responses was used for EFA, and another 223 responses were used for CFA. Construct validity was tested through these analyses, and convergent validity was assessed by examining the correlation with instruments measuring nursing informatics competency and self-leadership. Internal consistency reliability was confirmed with a Cronbach α of 0.95.

The final tool developed through this study consists of 29 items across 4 factors: 8 items for the ability to use digital technology, 5 items for digital safety management, 8 items for a digital collaboration mindset, and 8 items for organizational influence. The tool uses a 5-point Likert scale for self-report surveys, with a total score range from 29 to 145 points. Higher scores indicate a higher level of digital leadership among clinical nurses. Overall, the developed scale demonstrated strong reliability and validity for assessing digital leadership in clinical nursing practice. However, the tool did not fully satisfy the criteria for discriminant validity. Even when variables are used as conceptually independent constructs, correlations between related factors are common in practice [29]. This is consistent with findings from a study on the development of an integrated nursing leadership scale for Korean nurses [41], which also reported overlaps among constructs such as data management and communication technologies. In particular, relatively high correlations were observed between the ability to use digital technology and organizational influence, as well as between digital collaboration mindset and organizational influence. These results suggest that while the factors are conceptually distinct, they may be closely related in actual clinical settings where digital competencies are integrated with leadership behaviors. Although some aspects of discriminant validity were supported, these findings indicate that the boundaries between certain factors were not clearly distinguished. Despite these limitations, this tool has the advantage of including items that measure competencies needed to adapt to rapidly changing digital health care environments, such as work performance, learning, and adaptability [42]. Accordingly, future research is needed to more clearly distinguish the unique conceptual domains measured by each factor. Furthermore, the “digital safety management” factor included fewer items compared to other factors. Given the importance of patient safety and information security in digital health care environments, future research should consider expanding and refining items in this domain to enhance the comprehensiveness of the scale.

Given that leadership competencies required in digitally transforming health care environments are increasingly complex and diverse [13], this DLS-CN reflects the unique characteristics of Korean clinical settings and is the first scale of its kind to undergo statistical validation. Nevertheless, because data collection was conducted via an online survey using convenience sampling, caution is needed when interpreting the results. Additionally, the scale was developed for general clinical nurses and excluded nurses with less than 1 year of experience, nurse managers not involved in direct care, and those in administrative or educational roles, thereby limiting its generalizability. Moreover, the study did not include test-retest reliability, which represents another limitation.

Based on these findings, several implications can be drawn. In particular, the developed digital leadership scale should be applied to nurses from diverse countries and cultural backgrounds, as well as to nurses in various roles and settings, such as hospitals, community health centers, and educational institutions. Repeated studies are recommended to verify the reliability and validity of the instrument in diverse environments.

Future research should use this tool to assess digital leadership levels and develop tailored educational or intervention programs that enhance digital leadership according to workplace and contextual characteristics.

In addition, as this scale may be applicable not only to health care professionals but also to professionals in management, public administration, and related fields, further research should explore its broader applicability across disciplines.

The DLS-CN, developed through this study, is a systematic tool designed to measure and evaluate digital leadership among nurses in clinical practice settings. The DLS-CN consists of 4 core domains: ability to use digital technology, digital safety management, digital collaboration mindset, and organizational influence. It proposes a new standard for nursing leadership in health care environments driven by digital technologies.

In particular, the tool is useful for developing various educational programs aimed at identifying emerging nurse leaders and enhancing the digital leadership of clinical nurses in hospital environments where frequent changes in digital health care systems, technologies, and organizational structures occur. Furthermore, the development of this tool confirms that digital leadership extends beyond the mere acquisition of digital skills, encompassing the competence of clinical nurses to actively engage in and lead change. This is a meaningful contribution to the study.

Since this tool was developed based on data collected from clinical nurses in South Korea, and the items were created accordingly, further validation studies are needed in diverse health care settings and across cultural contexts. In the rapidly evolving digital health care environment, this tool can serve both as a foundational resource and a structured instrument for strengthening clinical nurses’ digital leadership.