The Stanford Chronic Disease Self-Management Program (CDSMP) is a valuable educational resource for supporting patients’ self-management behaviors. However, no evidence supporting its effectiveness in the Saudi Arabian population exists. Therefore, this study aimed to evaluate the effectiveness of the 6-month CDSMP in individuals with chronic conditions in Saudi Arabia within a primary care context. A quasi-experimental design was conducted in 110 adults living with ≥1 chronic disease in Saudi Arabia. The patients in the experimental group (n = 45) participated in a six-session CDSMP, whereas those in the control group (n = 65) continued their usual care. Baseline and 6-month assessments were conducted using relevant questionnaires to assess outcome measures. Analysis of covariance revealed that the participants who underwent the CDSMP had significantly higher self-efficacy levels in managing their conditions (F = 9.80, p < 0.01) and a greater tendency to adopt healthy behaviors to successfully manage their chronic illnesses (F = 11.17, p < 0.01). The participants who underwent the CDSMP also showed significant improvements in all health-related outcomes compared with those in the control group (p < 0.01). These findings indicated that the program had a positive effectiveness in self-efficacy, self-management behaviors, and health-related outcomes among adults with chronic diseases in Saudi Arabia. The CDSMP may be integrated into primary care settings to help patients successfully manage their chronic conditions.

Objectives: To explore nursing students’ perceptions and understanding of artificial intelligence (AI), aiming to identify and address critical knowledge gaps to support effective integration into educational practices. Methods: An exploratory qualitative study was carried out using semi-structured interviews with 20 nursing students from King Saud University, Riyadh, Saudi Arabia, in October 2023. Data collection focused on their definitions, conceptualizations, and perspectives regarding AI in healthcare. Results: A total of 3 key themes emerged: I)transformation, where AI represents a shift in nursing education from traditional methods to technological integration; II) power, viewing AI as a driver of knowledge creation and scientific advancement; and III) use of technology, focusing on AI applications to enhance efficiency, automate tasks, and augment human abilities across sectors. Conclusion: The study highlights the need to integrate AI-related content into nursing curriculum, preparing students for its application in healthcare. These insights emphasize AI’s role in shaping the future of nursing education and practice.

Introduction: Artificial Intelligence (AI) is a transformative force in nursing education, applicable in academic and clinical settings. It equips nursing students with skills to evaluate and apply AI in future patient care, preparing the nursing workforce for a healthcare landscape increasingly supported by AI. However, lack of studies focus on nursing students as AI users and the behavioural intention to accept and utilise AI. Aim: This study investigated the factors influencing nursing students’ acceptance and use of AI based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Materials and Methods: A cross-sectional study was conducted at one of the oldest and most prominent universities, collecting data from April to May 2022. The survey included 213 nursing students and aimed to evaluate the influence of the four UTAUT constructs- Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC)- on behavioural intention and usage behaviour. Additionally, the study explored the moderating effects of age and gender on the UTAUT model. Data were analysed using Statistical Package for the Social Sciences (SPSS) version 29.0 for descriptive statistics and SmartPLS version 4 for Partial Least Squares (PLS) structural equation modeling. Results: The findings indicated that PE positively influenced the behavioural intention of nursing students to adopt and use AI in nursing education. Regarding moderation effects, age moderated the relationship between PE and behavioural intention, whereas gender did not exhibit any moderation effect. Conclusion: This study provides a foundation for its integration to enhance learning outcomes and prepare students for technology-driven healthcare. It highlights the importance of evidence-based strategies tailored to meet diverse educational needs, ensuring effective adoption and utilisation.

Background: The concept of empowerment originated from the social sciences in the twentieth century. The concept was adopted in nursing to increase the professional progress of nursing sciences. The concept of empowerment is used in nursing as two constructs: structural and psychological. Objectives: The purpose of this paper is to perform a concept analysis of structural empowerment from a nursing perspective. Methods: Walker and Avant’s method of concept analysis was used Results: Autonomy and influence are considered major attributes of the structural empowerment concept in nursing. The method used for concept analysis provided purposeful clarification of the concept and confirmed the findings of the analysis. Conclusion: Structural empowerment in nursing has contributed positively to nurses, patient care, and organizations. It is linked to better quality effects, patient safety, and work effectiveness. Among leadership, it is associated with enhanced role satisfaction. Both inside and outside of organizational contexts, educational programs should play a part in developing empowerment since empowered nurses are more inclined to exercise skills like decision-making, problem-solving, and caregiving. Entail instructional programs to foster critical thinking, leadership, and better comprehension of nursing.