Background: Learning engagement, motivation and academic achievement are vital growing areas in academic research. Evidence suggests that students’ engagement and motivation are positively linked to improved quality of learning. However, limited number of research studies have been conducted within this scope. Therefore, the present study was conducted to investigate the relationship of learning engagement, motivation and academic performance among university nursing students. Participants and Methods: A descriptive design, with a comparative correlational approach for data analysis, was used to describe and compare study outcomes. Data was collected from 425 students at King Saud bin Abdul-Aziz University for Health Sciences campuses in Riyadh, Jeddah and Alhasa. Study instruments included background data sheet, students’ engagement in schools (SESQ-ENG), engagement facilitators (SEI), academic motivation (AMS), and academic achievement as measured by cumulative and last semester grade point average (cGPA, sGPA). Results: Overall, level of engagement was moderate (mean = 3.70± 0.63) with significant differences among campuses (F = 18.88, p≤ 001). Students’ perceptions of engagement facilitators and academic motivation were high (mean= 2.98 ± 0.49, 4.89 ± 1.03, respectively), and both varied by campus (F=6.35, p=0.002, F=9.85, p≤ .001, respectively). Engagement, motivation, and academic achievement showed medium to large correlations (i.e., between 0.20 and 0.63). Multiple regression equation including age, academic progress, academic engagement, motivation and engagement facilitators significantly explained 24% of variance in cGPA (F (5, 226) =14.209, p < 0.001) and 22% of the variance in sGPA (F (5, 214) = 12.202, p < 0.001). Conclusion: This study showed significant associations of students’ engagement, facilitating conditions (e.g., engagement-fostering aspects), and students’ motivation with significant effect on academic achievement. It is hoped that findings of this study could be used as quality indicators to direct school efforts towards achieving excellence in nursing education.

Background: Patients with heart failure (HF) are at high risk of readmission, contributing to substantial healthcare costs. This study investigated machine learning (ML) approaches to predict HF readmissions. Methods: A systematic review was conducted using several medical databases, adhering to the PRISMA guidelines, to identify studies employing ML to predict HF readmissions. Three reviewers independently screened the articles and extracted data. Results: Twenty-two studies from six countries were included in this study. Some studies examined 30-day readmissions, whereas others assessed 90-day, 180-day, or 1- to 3-year readmissions. Fourteen studies used supervised learning algorithms, with area under the curve (AUC) values ranging from 0.70 to 0.99, and unsupervised algorithms had AUCs of 0.69 to 0.72. The average age of the patients was 73 years, with approximately equal numbers of males and females. Conclusions: ML can predict HF-related hospitalization across various time frames. Supervised ML approaches and the incorporation of clinical knowledge may enhance model performance. Collaboration between providers and data scientists is needed to improve patient outcomes and reduce costs by using more accurate predictive models.

Background: The Saudi Arabian health care sector is transforming under Vision 2030 with the goal of digitizing its services. This necessitates a digitally prepared nursing workforce; however, there is evidence suggesting that nursing students have limited informatics competency and that these skills are minimally covered in their training programs. Objective: This study measured the baseline informatics competency and technology self-efficacy of undergraduate nursing students at the University of Hail, Saudi Arabia. Methods: Using a descriptive cross-sectional design, data were collected from 243 undergraduate nursing students at the University of Hail through an online survey. The survey measured demographics, informatics competency (Canadian Nurse Informatics Competency Assessment Scale), and digital technology self-efficacy. Data analysis used descriptive statistics, 2-tailed t tests, ANOVA, and hierarchical regression analysis. Results: Students reported a moderate level of informatics competency, with a mean Canadian Nurse Informatics Competency Assessment Scale item score of 2.57 (SD 0.84) on a scale from 1 to 4. They also showed moderate to high self-efficacy for digital technology, with a mean item score of 2.7 (SD 0.56) out of 4. Informatics competency scores were substantially higher in students with prior informatics training and frequent electronic health record exposure. In the underpowered exploratory hierarchical regression model, self-efficacy for digital technology showed a small positive association with informatics competency that approached statistical significance; however, the overall model was not statistically significant and explained only a limited proportion of the variance. Conclusions: This single-site study of undergraduate nursing students at the University of Hail found moderate self-reported informatics competency despite higher digital technology self-efficacy, indicating a need for strengthened informatics education to support the Saudi Vision 2030. While underpowered, exploratory analyses and self-report data mean that these institution-specific findings should be interpreted cautiously and used primarily to guide future multisite and mixed methods research.

Background: The integration of digital health technologies into nursing education in Saudi Arabia requires reliable tools to assess nursing informatics competency and digital technology self-efficacy among students. Objective: This study aimed to evaluate the reliability and validity of the Canadian Nursing Informatics Competency Assessment Scale (C-NICAS) and Digital Technology Self-Efficacy (DT-SE) scale among undergraduate nursing students at a Saudi university. Methods: A descriptive cross-sectional survey of 243 undergraduate nursing students at the University of Ha’il was conducted using the C-NICAS and DT-SE. Internal consistency was examined using Cronbach α, and construct validity was assessed using exploratory and confirmatory factor analyses. Results: A total of 243 students participated (mean C-NICAS score 54.0, SD 16.9; mean DT-SE score 2.7, SD 0.56). Both scales showed good internal consistency (C-NICAS total α=0.90; DT-SE α=0.80). C-NICAS demonstrated a multidimensional factor structure with an acceptable model fit (comparative fit index=1.00; root mean square error of approximation=0.081), whereas DT-SE showed a 3-factor structure with a suboptimal confirmatory model fit (comparative fit index=0.76, root mean square error of approximation=0.146). Conclusions: The C-NICAS and the DT-SE are suitable for assessing informatics competency and digital self-efficacy among undergraduate nursing students at this institution, although further refinement of the DT-SE may improve model fit. These validated tools can inform curriculum reform at this and similar institutions in Saudi Arabia and support the digital health goals of Saudi Vision 2030.

BACKGROUND The Saudi Arabian healthcare sector is transforming under Vision 2030, with the goal of digitizing services. This necessitates a digitally prepared nursing workforce; however, evidence suggests that nursing students have limited informatics competency, and these skills are minimally covered in their training OBJECTIVE To measure the baseline informatics competency and technology self-efficacy of Saudi undergraduate nursing students METHODS Using a descriptive cross-sectional design, data were collected from 243 undergraduate nursing students from Hail University via an online survey. The survey content covered demographics, informatics competency (Canadian Nurse Informatics Competency Assessment Scale), and digital technology self-efficacy. Data analysis employed descriptive statistics, t-tests, analysis of variance, and hierarchical multiple regression analysis RESULTS Students reported a moderate level of informatics competency, with a mean Canadian Nurse Informatics Competency Assessment Scale score of 2.16 (out of 4). They also showed moderate-to-high self-efficacy for digital technology, with a mean score of 2.7 (out of 4). Competency informatics scores were significantly higher among students with prior informatics training and frequent electronic health record exposure. Additionally, self-efficacy for digital technology was positively associated with informatics competency CONCLUSIONS There is a substantial gap between the informatics competencies of Saudi undergraduate nursing students and the expectations of Vision 2030. The findings indicate the need for improvements in informatics training and clinical electronic health record experience in the nursing curriculum to create a digitally competent workforce in the future CLINICALTRIAL NA

Background: The Blackboard is a course management system that provides educational materials, and grades; however, it is mostly limited to these functions. Conversely, it can be useful in enhancing students’ cognitive skills if used properly. This study aimed to assess the effectiveness of Blackboard as a teaching tool to enhance clinical reasoning skills among nursing students at King Saud bin Abdulaziz University for Health Sciences, (KSAU-HS), Jeddah, Saudi Arabia and to evaluate students’ feedback regarding the utilisation of Blackboard as an educational tool. Methods: This is a quasi-experimental, single-group pretest–posttest study which included 38 participants. Two Blackboard forums were created: (1) case study, (2) debriefing. The researcher looked at students’ grades on the first and second clinical evaluation and on the first and second clinical assignments before and after using the Blackboard to compare their performance on higher cognitive skills. T-test inferential statistic was used to determine the significant difference and it was set at p value of ≤ 0.05. Focus group interview was conducted to obtain deeper explanations from students’ perspectives about the new intervention to understand perceived challenges and positive aspects. Results: The statistics demonstrated a considerable improvement in students' grades in high cognitive areas such as critical thinking and clinical reasoning after using the Blackboard forums compared to the initial grades, as follows: (1) the clinical evaluation with a score of t = 13.4, p < 0.001* and (2) the clinical assignment with a score of t = -17.5, p < 0.001*. The qualitative findings were compatible with this as most of participants reported positive impact of Blackboard on their aquired knowedge and acknowedged its flexibility. Conclusion: Blackboard facilitated group learning by encouraging active discussion and exchange of knowledge. It provides an asynchronous interactive learning experience with being cost efficiently. Data showed several beneficial qualities for Blackboard in improving higher cognitive skills and supporting different learning styles. Eventually, it provides a unique opportunity for instructors and students to debate advances in their respective fields while receiving the required technological support.