The relationship between digital literacy and clinical decision-making skills among student nurses: a cross sectional study

Abstract

Introduction

In an increasingly technology-driven healthcare environment, digital literacy and clinical decision-making (CDM) are essential competencies for undergraduate nursing students. This study investigates the relationship between digital literacy and clinical decision-making skills among student nurses.

Methods

A cross-sectional correlational design was employed, involving a convenience sample of 201 undergraduate nursing students at Taif University, Saudi Arabia. Data were collected on campus between August and September 2025 via a secure Google Forms link distributed through official university channels. Analysis included descriptive statistics, independent t-tests to examine sex differences, and Pearson’s correlation and linear regression to evaluate the relationship between variables.

Results

The nursing students possessed a high level of digital literacy (M = 51.00, SD = 8.44) and a high level of clinical decision-making ability (M = 171.30, SD = 12.60). Female students (M = 51.78) scored significantly higher in digital literacy than male students (M = 44.97), with t(199) = 3.65, p < 0.001. A statistically significant positive correlation was found between the two variables (r = 0.389, p < 0.001), indicating that higher digital competency is associated with stronger clinical decision-making skills. Digital literacy was a significant predictor, accounting for approximately 15.1% (R² = 0.151) of the variance in CDM scores. Sex differences were highly significant across both domains. Female students reported significantly higher mean digital literacy scores (51.78, SD = 7.73) compared to their male counterparts (44.97, SD = 7.89; t = -3.87, p < 0.001). Furthermore, a significant disparity was observed in clinical decision-making, where female students scored 172.50 (SD = 12.40) compared to 162.03 (SD = 14.15) for males (t = -3.82, p < 0.001).

Conclusion

The findings underscore the critical role of digital literacy in clinical performance. The results suggest a need for targeted educational strategies to bridge sex-based competency gaps within nursing education. This ensures all students are prepared for a digitalized healthcare landscape.

Introduction

Digital literacy and clinical decision-making skills are essential skills for nursing undergraduates in this era of technology-led healthcare settings, where developments in technology happen at an ever-increasing pace. Digital literacy refers to the skills required to successfully use technology [1, 2, 3]. Concurrently, effective patient care demands strong clinical decision-making (CDM) skills [4, 5]. This complex process requires nurses to have the knowledge to assess patient information, use evidence in practice, and demonstrate critical thinking to make sound decisions regarding health. These consolidating features of healthcare activities confirm the need for digital literacy to inform effective clinical practice due to advancing technological aspects. This underscores the importance of these processes, particularly for student nurses, as they prepare for their future work in an increasingly technologically oriented healthcare environment [6, 7].

The transition from theoretical understanding of technological skills to their application in practice remains a difficult task for many nursing undergraduates [8], and this relationship requires further investigation. What has been established in these areas to date shows that there is a differing understanding of and skill in the area of digital literacy by undergraduate students in nursing [8, 9]. Further, this raises questions regarding the gap between what students believe are their abilities and their actual skills, especially in relation to patient care in practice. For example, while many nursing students demonstrate a reasonable level of digital literacy, there is evidence that this does not necessarily translate into clinical decision-making skill [8]. Prior studies have also shown the necessity for specific education to improve digital competencies in nursing curricula; however, few studies have examined how these competencies impact specifically clinical decision-making practice [5, 10]. This demonstrates an important empirical gap, as the means by which digital literacies affect nursing students’ clinical judgment needs more attention.

This study is guided by a theoretical framework based upon the Technology Acceptance Model (TAM). According to the TAM, the perceived ease of use and perceived usefulness of technology have a considerable impact on the intention of persons to accept a specific technology [6, 1]. This intention to use digital tools in the clinical setting—driven by positive perceptions of ease and usefulness—reflects the capabilities and confidence levels one possesses to properly assimilate information and technology into patient assessments, data interpretations, and critical thinking. The model suggests that nursing students’ perceptions of digital tools significantly affect their clinical decision-making [8, 11]. In presenting digital literacy to nursing students, educators must highlight the real-world advantages that information technology offers for enhancing patient care. Furthermore, preparing students involves teaching them how digital competency psychologically affects their confidence in utilizing technology, ensuring they are better equipped for the complex realities prevailing in the current healthcare arena.

The importance of this study relates to its ability to close existing gaps between digital literacy and clinical decision-making among student nurses. It is crucial that modern nurses are taught the skills necessary to incorporate digital applications in their practices, since they will definitely permeate nursing in the future [12, 7]. This study will also identify necessary curricular changes and structural incentives needed so that digital literacy skills may be more fully embraced in clinical decision-making processes. By delineating how digital literacy affects the clinical decision-making skills of nursing students, this study enables educational practices that improve clinical outcomes among the next generation of nursing professionals. Therefore, it aims to investigate the relationship between digital literacy and clinical decision-making skills among student nurses.

Methods

Study design

A quantitative, cross-sectional correlational design was utilized to explore the relationship between digital literacy and clinical decision-making skills among undergraduate nursing students.

Population and sampling

The sample size was determined a priori using GPower with a one-way analysis of variance (ANOVA) for three independent groups. With parameters set for average effect size (f = 0.25), alpha level of 0.05, and statistical power of 0.80, the recommended minimum sample size was 159 students (approximately 53 in each group). To allow for potential non-respondents and participant attrition, the target sample size was increased by 15%, resulting in an adjusted requirement of 182 participants. The 201 students enrolled in nursing courses were included, with each academic level group (third, fourth year, and interns).

A non-probability convenience sampling approach was utilized. While the study targeted specific academic levels (third-year, fourth-year, and interns) to ensure clinical exposure, participants were recruited based on their availability and willingness to participate during the data collection period. Participants were recruited from Taif University using announcements in prescheduled academic periods and through official university electronic means. Eligibility for participation included enrollment in the third year through internship of the undergraduate nursing programs and the completion of at least one clinical rotation. The exclusion criteria were first-year and second-year nursing students with no clinical experience, and those who refused to participate. Data was collected on campus during regular academic time between August and September 2025.

Instruments

This research employed a thorough data collection strategy structured around three main sections. These included a Demographic Profile and two important psychometric explorations. The Demographic Profile was used to collect relevant background data on the participants. There are two validated instruments that were designed to measure the core variables under investigation. A pilot study was first conducted with 30 nursing students to evaluate the clarity and reliability of the research instruments, resulting in Cronbach’s alpha ≥ 0.80.

The first of the two validated instruments was the Nursing Digital Application Skill Scale (NDASS), a 12-item scale developed by Qin and colleagues [13] to measure nurses’ skillfulness in using digital applications. The measurement was at a response level using a 5-point Likert-type scale, that is, 1 = strongly disagree, to 5 = strongly agree. The NDASS had good psychometric quality, as evidenced by a very high content validity index (0.975), strong internal consistency (Cronbach’s α = 0.968), and high composite reliability (0.964). Furthermore, a confirmatory factorial analysis supported the presence of a high-order one-factor solution, which accounted (collectively) for 74.8% of the total observed variance [13].

Participants’ perception of their clinical decision-making abilities was obtained using the Clinical Decision-Making Scale in Nursing (CDMNS), by Jenkins [14]. This 40-item self-reported questionnaire aims to measure the mental processes of clinical reasoning through four sub-scales: (1) Search for Alternatives or Options, (2) Canvassing of Objectives and Values, (3) Evaluation and Re-evaluation of Consequences and (4) Search for Information and Assimilation of New Information. The items used a 5-point Likert-type scale (1 = Never, 5 = Always). To keep the reverse-worded item scores (e.g. I find it difficult to identify alternatives when making a decision) in the overall total score direction, 18 negatively worded items were reverse coded and scored in the following way: a response of 5 became a 1 and a response of 1 became a 5. The total score range between 40 and 200. Higher total scores indicate a stronger perception of their clinical decision-making ability [14].

The NDASS and the CDMNS show sufficient psychometric properties and adequate content relevance for the target population. In order to determine whether the instruments were technically and contextually accurate, the content validity was thoroughly evaluated by a panel consisting of two nursing informatics researchers and a nurse informaticist. This expert panel substantiated that the items reflected the nexus of digital skills and clinical reasoning. The NDASS had outstanding Content Validity Index and internal consistency (Cronbach’s alpha = 0.968) and the CDMNS also was reliable (Cronbach’s alpha = 0.851). The preliminary pilot study (n = 30) also contributed to the body of knowledge, with a Cronbach’s alpha 0.80, indicating that the instruments are stable and valid for nursing research in the context of the study.

Data collection procedure

The Taif University Review Board approved the study. The eligible students were contacted to participate using a secure Google Forms link distributed through the university’s official channels. The survey was available for two weeks, with a mid-survey reminder.

Statistical analysis

Data analysis was performed using IBM SPSS Statistics (Version 30). Descriptive statistics (frequencies, means, and standard deviation scores) were provided for the NDASS and CDMNS scores. A Pearson correlation was used to determine the correlation between digital literacy and clinical decision-making. Student’s t-tests were used to compare the means between sex and age. One-way ANOVA was used to determine the differences between groups of academic years; post-hoc testing was not performed because no significant difference was found between groups. All tests were two-tailed and analyzed at a 95% confidence level or less.

Ethical considerations

The research plan was in accordance with the guidelines established in the Declaration of Helsinki. Institutional Review Board approval was obtained from Taif University prior to the recruitment of the research subjects. Participation was voluntary, and written informed consent was obtained prior to the start of the survey. Anonymity and confidentiality were assured as participants provided only non-identifiable data, results were presented in aggregate form, and participants were allowed to withdraw from the study at any time and for any reason without any penalty. To guarantee confidentiality, anonymous replies to the survey were assured, and data were stored in separate encrypted files that could only be accessed by the research team. All data were stored in encrypted files that could be accessed only by the researcher.

Results

Table 1 presents the demographic characteristics of the nursing students. Of the 201 participants, most were aged ≤ 21 years (80.1%), while 19.9% were older than 22 years. The sample was predominantly female (88.6%), with males representing only 11.4%. In terms of year level, the majority were in their third year (86.1%), followed by smaller proportions in the fourth year (10.4%) and interns (3.5%).

Table 1.

Demographic profile of nursing students (n = 201)

Variable	Category	Count (n)	Percentage (%)
Age (years)	≤ 21	161	80.10%
	> 22	40	19.90%
Sex	Male	23	11.40%
	Female	178	88.60%
Year Level	Third Year	173	86.10%
	Fourth Year	21	10.40%
	Internship	7	3.50%

Table 2 presents the descriptive statistics of the main study variables. The mean score for overall digital literacy was 51 (SD = 8.44), with scores ranging from 12 to 60. For overall clinical decision-making, the mean score was 171.30 (SD = 16.52), with a minimum of 40 and a maximum of 200.

Table 2.

Descriptive statistics of overall digital literacy and clinical decision-making scores

Variable	Mean (SD)	Minimum	Maximum
Overall Digital Literacy	51(8.44)	12	60
Overall Clinical Decision-Making	171.30 (16.52)	40	200

Abbreviation: SD=Standard Deviation

Table 3 shows the correlation between digital literacy and clinical decision-making. A statistically significant positive correlation was found between the two variables (r = 0.389, p < 0.001, 95% CI [0.265, 0.501]). This indicates that higher levels of digital literacy were associated with stronger clinical decision-making ability. The coefficient of determination (R² = 0.151) suggests that digital literacy explained approximately 15.1% of the variance in clinical decision-making among nursing students as shown in Fig. 1.

Table 3.

Correlation between digital literacy and clinical decision-making

		Clinical Decision making	95% CI
Digital literacy	Pearson Correlation	0.389**	0.265 − 0 0.501
	P-value	< 0.001
	N	201

**. Correlation is significant at the 0.01 level (2-tailed)

Fig. 1.

Scatter plot of digital literacy versus clinical decision-making

As shown in Table 4, there were no significant differences in digital literacy or clinical decision-making scores between the two age groups. Students aged ≤ 21 years had a mean digital literacy score of 51.05 (SD = 8.04) compared to 50.32 (SD = 8.11) among those aged > 22 years (t = 0.53, p = 0.600). Similarly, when adjusted to the 40-item scale, clinical decision-making scores did not differ significantly by age, with means of 158.48 (SD = 15.06) and 159.61 (SD = 18.92), respectively (t = − 0.38, p = 0.705).

Table 4.

Comparison of digital literacy and clinical decision-making scores by demographic characteristics

Variable	n	Digital Literacy Mean (± SD)	t/F	p-value	CDM Mean (± SD)	t/F	p-value
Age (years)ᵗ			0.53	0.6		-0.38	0.705
≤ 21	161	51.05 (8.04)			170.80 (12.45)
> 22	40	50.32 (8.11)			173.31 (13.12)
Sexᵗ			-3.87	< 0.001*		-3.82	< 0.001*
Male	23	44.97 (7.89)			162.03 (14.15)
Female	178	51.78 (7.73)			172.50 (12.40)
Year Levelᶠ			2.79	0.064		0.96	0.383
3rd Year	173	50.93 (8.39)			171.05 (12.50)
4th Year	21	49.03 (4.04)			172.15 (11.80)
Internship	7	57.19 (2.49)			174.90 (13.20)

Note: t indicates Student’s t-test; F indicates one-way ANOVA. SD = Standard Deviation

An independent samples t-test was conducted to compare digital literacy levels between sexes. The results revealed a significant difference, with female students (M = 51.78, SD = 8.12) scoring higher than their male counterparts (M = 44.97, SD = 9.05); t(199) = 3.65, p < 0.001. These findings suggest that sex significantly influences digital literacy, specifically that female nursing students outperform males in this domain. Similarly, an independent samples t-test was employed to determine if differences existed in perceptions of clinical decision-making (CDM). The analysis indicated that female students reported significantly higher CDM scores (M = 172.50, SD = 12.40) than male students (M = 162.03, SD = 14.15). This difference was statistically significant, t(199) = 3.82, p < 0.001, suggesting that female nursing students perceive their clinical reasoning abilities more strongly than their male peers.

Lastly, no significant differences were observed across year levels (3rd year, 4th year, and Internship) for either digital literacy (F = 2.79, p = 0.064) or clinical decision-making (F = 0.96, p = 0.383). Mean scores for clinical decision-making across levels ranged from 154.59 to 161.28, reflecting consistent performance regardless of academic year.

Discussion

On digital literacy and clinical decision-making

This study focused on the relationship between digital literacy and clinical decision-making in student nurses. The mean score for overall digital literacy indicates a high level of proficiency among participants. Similarly, the mean score for clinical decision-making was at a comparably high level. These figures indicate that participants demonstrated a high baseline of digital literacy. However, there remains a critical need for specialized advancement. This is especially true given the increasing dependence on complex digital technologies in healthcare. The implications of these findings are noteworthy, particularly in the context of current literature.

Studies have previously indicated the positive effects of digital health literacy interventions. Specifically, these interventions improve self-efficacy in navigating digital health resources, which enhances decision-making ability [15]. This raises a need for educational interventions to overcome the digital literacy gap. Such interventions would enhance the clinical decision-making strategies of both healthcare workers and patients. However, current research also indicates a relationship between digital health literacy and the ability to evaluate online health information critically. It is further documented that many people have self-reported confidence in accessing digital health resources. Despite this, they express less self-confidence in using them appropriately for decision-making [16]. This is underlined by evidence that those with higher digital health literacy find it easier to cope with health issues. Consequently, greater levels of digital literacy would improve clinical outcomes [17]. In contrast to previous findings, these results accentuate the interdependence of digital literacy and effective health management. For example, research undertaken during the COVID-19 pandemic indicated that the digital health literacy of parents strongly impacted their engagement with virus-related information [16]. This further highlighted the relationship between digital literacy and health status. It indicates an urgent need to enhance these skills to facilitate better accessibility to healthcare and standards of care.

In addition, the findings relating to clinical decision-making agree with studies on digital health literacy interventions. For example, Fitzpatrick speaks of enhancing digital health literacy and self-management through digital communications [3]. These skills are critical to clinical decision-making. This indicates the dual impact of digital and clinical decision-making skills in effecting enhanced health levels across various populations.

Correlation between digital literacy and clinical decision-making

The results of this study show a statistically significant positive relationship between digital literacy and clinical decision making. This means that increased digital literacy in nursing students correlated with better clinical decision making. This relationship has a coefficient of determination which shows that about 15.1% of the variance in clinical decision making can be accounted for by digital literacy. The results of this study show a statistically significant positive relationship between digital literacy and clinical decision making. This relationship has a coefficient of determination which shows that about 15.1% of the variance in clinical decision making can be accounted for by digital literacy. These findings align with the core tenets of the TAM, specifically the relationship between a user’s capabilities and their intention to utilize digital tools for job performance. The fact that digital literacy explained 15.1% of the variance in CDM scores indicates that when students possess the necessary digital skills, they are better equipped to realize the perceived usefulness of technology in the decision-making process. Consequently, improving digital literacy may directly lower the barriers to perceived ease of use, fostering a more seamless integration of informatics into clinical practice. As the healthcare arena continues to integrate digital technologies, the need to understand the implications of this relationship becomes a necessity. As the healthcare arena continues to integrate digital technologies, the need to understand the implications of this relationship becomes a necessity. Digital literacy contains a wide variety of skills necessary to facilitate the proper use of digital resources and platforms in healthcare and other areas. Therefore, digital literacy can be defined as including technical skills necessary to efficiently use digital platforms as well as being able to evaluate and utilize health information efficiently [18]. This concept ties in with the concepts presented above viewing digital communication tools as helpful to improving digital health literacy and greater health outcomes from improved clinical decision making processes [3]. The combination of skill development presented in the above studies indicates that efforts to develop digital literacy can empower tomorrow’s healthcare artists in being able to make better informed clinical decisions related to health outcomes. In addition, the positive relationships identified in this study reflect findings in the literature supporting nursing and healthcare professionals need to have solid eHealth literacy [19]. found that individual eHealth literacy has a significant impact on health-related decisions and lifestyle choices. Consequently, great emphasis must be placed on the need for education to incorporate digital literacy education into health educational curricula. Likewise, the study conducted by [7] also supports these findings revealing a direct relationship between digital health literacy and nursing students, ability to evaluate and use health info critically [7].

While the existing literature has indicated a natural positive influence of traditional health literacy on decision-making ability, an important parallel can be drawn from these findings. This also identifies the current implications that occur in digital platforms—an area often overlooked by studies focusing solely on traditional health literacy. This will allow for essential gaps that may occur in the understanding of decision-making in the digital age of eHealth. The results of the previous study highlight the crucial role of digital literacy skills in project-based learning intervention contexts, underscoring the need for change in education. This change will enable the next generation to develop competency in digital skills, thereby enhancing their ability to make informed decisions [20]. The increase of this competency will enable educational arenas to prepare future healthcare practitioners to navigate the complexities of new healthcare environments. Not only will this create a foundation of education consistent with digital trends, but it also has the potential to improve clinical outcomes and address patient safety issues across the board in a complex, evolving digital world. Follow-up studies must be done in the longitudinal vein from here, assessing the impacts of digital literacy intervention training on clinical decision-making skill development and overall health outcomes.

Comparison of digital literacy and clinical decision-making scores by demographic characteristics

The results indicating no significant differences in digital literacy (NDASS) and clinical decision-making (CDMNS) scores according to age suggest that cognitive factors associated with increasing age may not be as significant in this context as traditionally assumed. This findings-based differential effect resonates with existing literature debating the role of age in decision-making processes. Research indicates that certain cognitive processing skills, such as those involved in encoding and risk, may differ across age groups rather than being inherently superior in one over the other [21, 22]. Furthermore, while cognitive processing among the aged is truly differentiated, younger students may perform equivalently in tasks of clinical decision-making and digital literacy due to contextual learning and frequent exposure to technology [21, 22].

In contrast, the significant differences found in females—indicating statistical superiority over males in both digital literacy and clinical decision-making skills—align with the broader scholarly discussion suggesting that sex may have a greater influence on success in these pursuits than gender. While some literature suggests that females may possess greater capability in communication and collaborative skills which can enhance clinical decision-making [23–25]. However, it is essential to note that the sample was predominantly female (88.6%, n = 178) compared to a much smaller male representation (11.4%, n = 23); thus, these findings should be interpreted with caution regarding the representativeness of the male subgroup. Instead, this performance gap likely reflects a complex interplay of non-deterministic factors. Recent exploration indicates that females are now outperforming males in digital literacy [26] due to advancements in educational environments that better support diverse learning styles. Furthermore, these differences may stem from variations in prior technology exposure or levels of technological self-efficacy—the self-confidence in utilizing digital tools within a healthcare context. Finally, the collaborative nature of nursing education may align with specific social or environmental learning patterns that currently favor female students in this institution.

The lack of significance regarding year levels—where no score differentials were found for either digital literacy or clinical decision-making—indicates a possible need to view interventions and pedagogies in a different light. This lack of variability across year levels conforms with prior research such as that of Wu et al. [27] and Wu and colleagues [28] indicating that educational context and application may be more critical than mere time lapse or seniority. While some literature emphasizes the importance of clinical decision-making within the educational experience, this is not necessarily equitably transferable across different educational circumstances [29]. These findings imply that specialized educational contexts must be designed to enhance both digital literacy and clinical decision-making skills across sexes, while acknowledging that younger age does not inherently put students at a disadvantage. This suggests a need for a tailored methodology that addresses individual learning patterns as determined by age. Future studies should not only address possible sex inequities regarding technological and clinical training, but also the interaction of educational experiences that lead to these competencies and their improvement over time.

Study implications

The findings of the study have profound implications for nursing education, nursing practice and further research. From an educational point of view, the significant positive relationship of digital literacy with clinical decision-making indicates a need for comprehensive training in digital literacy to be included in the curriculum. This training should not be confined to teaching basic computer skills but should address the issues of critically evaluating health information and ethical management of data. Additionally, the significant sex difference evident in female students achieving higher scores than males in both areas indicates that directed educational interventions are required to address any possible barriers or skill deficit amongst male nursing students. The observation that scores are not different with regard to age or year level indicates that these are not skills or information that will come with maturation but there is a clear need for direct, formal teaching of these areas and the use of active learning strategies throughout the program. From a practice and policy point of view, consideration should be given in the health care institution to assessment of digital literacy before placement of new graduates for employment and establishment of Continuing Professional Development (CPD) programs to enhance the existing workforce’s ability to utilize digital literacy in tools such as Electronic Health Records (EHRs) and telehealth systems. Policies should encourage the active, critical use of easy to use digital tools for the support of clinical reasoning at the bedside. Finally, from the research perspective it is suggested that future studies are required to examine why there is a sex disparity and possibly correlate factors such as technology exposure or self-efficacy. Longitudinal and experimental studies are also required to establish a causal link between digital literacy intervention and improved clinical decision making and the mediation factors, such as critical thinking, that operate to account for the relationship.

Study limitations

While this research has yielded significant findings, several shortcomings must be acknowledged to provide a comprehensive view of the study outcomes. One primary limitation concerns the cross-sectional correlational design, which precludes causal inferences. Although there is an identifiable, positive correlation between digital literacy and clinical decision-making (CDM), it remains difficult to isolate the specific impact of digital literacy from the influence of skills developed concurrently. Future research should consider longitudinal designs or experimental models that integrate structured electronic literacy training directly into prescribed clinical skills.

Furthermore, there is a moderate to significant issue regarding the generalizability of findings due to the single-institution research design (Taif University). The outcomes of this study may not generalize to nursing students’ experiences in broader cultural or academic contexts. The participant sample also featured a large female majority (88.6%) and consisted of Level 3 students in 86.1% of instances. To address this, future research should span multiple institutions and sites to sample variables more equitably.

Regarding data collection, the use of self-reported measures introduced challenges related to social desirability and a potential lack of participant self-insight. Students may be better evaluated through methods that offer less opportunity for social desirability bias. Consequently, future research should utilize more structured, objective outcomes rather than open-ended self-reports, as the authors seek to move beyond basic literacy toward more robust digital literacy metrics.

Even though a significant correlation was established (p < 0.001), only a small portion of the variance in CDM was explained by digital literacy (^R2 = 0.151). This indicates that many influential factors were not accounted for in this study. Because this research did not employ multivariate analysis, there was no opportunity to control for confounding factors such as age, previous experience, or prior education. It is, therefore, vital for future researchers to utilize multiple regression analysis to manage these variables and explore potential mediating factors, such as critical thinking.

Finally, regarding the observed performance differences based on gender, it is important to avoid deterministic assumptions about innate ability. The disparity in sample sizes between genders may have disproportionately influenced the p-value. Future study should investigate external causes for performance differences—such as varied learning styles and attitudes toward technology—rather than treating these differences as an innate syndrome determined by gender.

Conclusion

The strong, positive correlation between digital literacy and clinical decision-making makes digital literacy a core skill that all nurses must develop and maintain. The data supports the need to formalize health informatics in every nursing curriculum—it highlights a critical sex disparity in that male students possess lower levels of competency. These programs are not merely advisable, they are vital policy initiatives that must be undertaken in order to provide for social equality and a level playing field for all nurses, and other health professionals, in order to provide full preparation for the requirements of modern health care.

Author contributions

MSA was responsible for the conceptualization, methodology, formal analysis, and writing of the original draft.

Funding

This research was funded by the Deanship of Graduate Studies and Scientific Research, Taif University. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study was conducted in accordance with the Declaration of Helsinki and was approved by the Ethics Committee of Taif University (Approval Number: HAPO-02-T-105). Informed consent was obtained from all individual participants involved in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.