Introduction: Healthcare-associated infections are a significant risk to patients and the healthcare system. Differences in knowledge, attitudes, and practices among nurses have limited standardized precautions. Improving self-efficacy can enhance compliance with standard precautions, protect patients, and preserve the credibility of healthcare institutions. Aim: This study aimed to determine the mediating effects of self-efficacy on nurses’ knowledge, attitude, and compliance with standard precautions in Saudi Arabia. Methods: This cross-sectional study was conducted in four hospitals in Dharan, Saudi Arabia, between July and October 2023. The respondents were selected through a multistage sampling of 305 nurses from wards and special areas. Results: participants demonstrated a moderate level of knowledge (M = 19.00, SD = 2.17), positive attitudes (M = 55.86, SD = 10.22), intermediate compliance (M = 72.44, SD = 11.47), and moderate self-efficacy (M = 29.99, SD = 11.40). Respondents who possessed more knowledge demonstrated positive attitudes toward standard precautions (r = 0.256, p < 0.001) and were more likely to comply (r = 0.376, p < 0.001). Higher self-efficacy levels were significantly positively correlated with knowledge (r = 0.391, p < 0.001), attitude (r = 0.311, p < 0.001), and compliance (r = 0.385, p < 0.001). The direct effect of knowledge on compliance was estimated to be 0.115 (p < 0.001), while the direct effect of attitude was slightly weaker (0.014, p = 0.049). Self-efficacy indirectly increased compliance through its influence on knowledge and attitude, with indirect effects of 0.039 (p < 0.001) and 0.008 (p = 0.002), respectively. Conclusions: Nurses with higher knowledge of infection control and positive attitudes toward established protocols were more likely to comply consistently. This association is further strengthened by self-efficacy. This confidence enhanced their understanding of the specific procedures, reinforced their positive beliefs about the importance of protocols, and ultimately led to greater adherence.

To explore how nurses in interprofessional hospital teams experience and negotiate professional autonomy within hierarchical decision-making environments. Nurse autonomy is essential for safe, patient-centred care, yet it is often constrained by institutional protocols, electronic order-entry systems, and interprofessional hierarchies. While international literature highlights systemic barriers, little is known about the subtle strategies nurses use to reclaim influence within team-based hospital contexts, particularly in Middle Eastern healthcare settings. A qualitative hermeneutic phenomenological design was employed, following COREQ guidelines. Seventeen registered nurses working in polyclinics affiliated with King Faisal University, Al-Ahsa, Saudi Arabia, participated in semi-structured interviews conducted. Data were analysed using reflexive thematic analysis, supported by NVivo 14. Ethical approval was obtained from the King Faisal University Institutional Review Board. Four interrelated themes emerged: (1) The invisible architecture of (de)autonomy, (2) Teamroom hierarchies and the choreography of voice, (3) Quiet resistance and boundary work, and (4) Conditions that enable nurse autonomy. Nurses described struggling with structural and cultural barriers but also revealed micro-autonomies, alliances, and advocacy practices that protected both patient safety and professional identity. Autonomy is not merely an individual trait but an organisational property shaped by policies, governance, and team dynamics. Leadership strategies that embed nurses’ voices into decision-making structures are critical for improving patient outcomes and professional well-being. Not applicable (qualitative study).

Allostatic load is pertinent to explain biopsychological phenomena affecting health outcomes in cancer research

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.

To explore how nurses in university-affiliated polyclinics interpret incident-analysis findings and translate them into feasible, sustainable practice changes. Incident reporting and analysis are widespread, yet the “audit-to-action” gap persists. Little is known about how frontline nurses in ambulatory services convert recommendations into reliable routines amid workload and resource constraints. Qualitative process evaluation with a focused ethnographic orientation, reported according to COREQ. Conducted across King Faisal University–affiliated polyclinics in Al-Ahsa, Saudi Arabia. Purposive sampling recruited registered nurses across roles. Data sources included semi-structured interviews, non-participant observation of safety huddles/quality meetings, and document review. Data were analyzed using reflexive thematic analysis, then mapped to implementation constructs to specify barrier→strategy pairings. Seventeen nurses participated. Four interrelated themes described the translation pathway: (1) From analysis to actionability—“taskifying” recommendations and using simple artefacts (checklists, prompts, brief scripts); (2) Feasibility in real time—uptake hinged on workflow fit, clear ownership, and minimal added paperwork under peak load; (3) Social infrastructure for change—leadership follow-through, psychologically safe huddles, and peer champions enabled adoption; and (4) Making change stick—balancing fidelity with local fit, maintaining regular feedback, and aligning resources/policies secured sustainment. Translating incident analyses into safer care requires small, engineered steps that protect feasibility and provide predictable feedback. Codifying core tasks, embedding prompts in existing workflows, and modest resourcing/policy alignment are practical levers for durable improvement in ambulatory nursing services. Findings provide practical guidance for nurse leaders on embedding safety recommendations into outpatient workflows through taskification, leadership follow-through, and psychologically safe huddles. Two patient partners and one caregiver reviewed the interview guide and contributed to theme interpretation on communication, safety, and experience. Not applicable (qualitative study).

Introduction: Caring behaviors are actions that prioritize the welfare of patients. Job satisfaction is one factor that can influence nurses' caring behaviors, as nurses with higher job satisfaction tend to exhibit more positive caring behaviors.Objective: The study aimed to assess critical care nurses' job satisfaction levels, explore the dimensions of their caring behaviors, investigate the relationship between their caring behaviors and job satisfaction, and identify the significant independent predictors of nurses' job satisfaction and caring behavior in critical care units.Method: The study used a descriptive-analytic, correlational, cross-sectional research design. It was conducted at the critical care units of King Fahd Military Medical Complex in Saudi Arabia. A convenience sample of 112 registered nurses completed an online survey that included the Job Satisfaction Survey and the Caring Behavior Inventory.Results: The majority of respondents fall under the category of Ambivalent job satisfaction, constituting 67.9% of the total nurses. The analysis indicated a moderate job satisfaction level and a high caring behavior among critical care nurses. The study found a positive correlation between nurses' job satisfaction and caring behaviors. Factors such as working hours, work unit, and years of experience were significantly associated with nurses' job satisfaction. However, factors like operational procedures, co-worker relationships, nature of work, and working hours were significant predictors of nurses' caring behavior.Conclusion: The study highlights the importance of addressing job satisfaction factors to enhance critical care nurses' caring behaviors, which can ultimately improve patient outcomes. Strategies to enhance nurses' job satisfaction and support their caring practices should be a priority for healthcare organizations